Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Office Action is in response to the amendments dated March 31, 2026.
Claims 1-4, 6-14, and 16-26 are pending.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1 and 11 are provisionally rejected on the ground of obviousness-type nonstatutory double patenting as being unpatentable over respective Claims 1 and 11 of copending Application No. 18/585,449 in view of Gormley et al. (US PGPUB 2021/0059607 – “Gormley”).
Claims 1 and 11 of the present patent application include all features found in respective Claims 1 and 11 of copending Application No. 18/585,449 (see chart below), except for the feature(s) of acquiring environment information with respect to a front-end portion of the endoscopic device, wherein the environment information includes structural information with respect to a body shape that characterizes a three-dimensional shape of a lumen of the lower gastrointestinal tract; and generating the first control signal comprises determining a steering direction and a steering magnitude that conforms to the three- dimensional shape of the lumen.
Gormley discloses acquiring environment information with respect to a front-end portion of the endoscopic device, wherein the environment information includes structural information with respect to a body shape that characterizes a three-dimensional shape of a lumen of the lower gastrointestinal tract (Gormley FIG. 11, articulated stylus 1118 having an imaging device – see Gormley paragraph [0134], passing through a lower gastrointestinal tract); and generating the first control signal comprises determining a steering direction and a steering magnitude that conforms to the three- dimensional shape of the lumen (Gormley FIG. 11, showing articulated stylet 1118 passing through a lower gastrointestinal tract; Gormley paragraph [0094], “The imaging device 108 may capture image data (“captured image data”) corresponding to structures (e.g., of the organ being traversed by the catheter tube 100) surrounding the distal end of the catheter tube 100. For example, LiDAR, time of flight imaging, visual image sensing (e.g., which may involve the capture of still images and/or video), or other applicable imaging techniques may be applied to capture the image data. Topographic image data that may be included in the captured image data may provide information related to the shape, volume, consistency, and location of the organ, or the portion of the organ, through which the distal end of the catheter tube 100 is traversing. The captured image data may be transmitted to and used by one or more artificial intelligence (AI) models executed by the remote device that is in wireless electronic communication with the transceiver 106, providing feedback to the AI model(s) regarding the location and position of the catheter tube 100 in the subject's body (e.g., in an organ thereof). Thus, the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100 and to continuously monitor the location of the catheter tube 100 once it has reached the target location”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Gormley’s acquisition of environment information with respect to a front-end portion of the endoscopic device, wherein the environment information includes structural information with respect to a body shape that characterizes a three-dimensional shape of a lumen of the lower gastrointestinal tract; first control signal that comprises determining a steering direction and a steering magnitude that conforms to the three- dimensional shape of the lumen with the invention claimed by co-pending Application No. 18/585,449. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a method/system that is applicable in a lower gastrointestinal tract (see Gormley FIG. 11).
Dependent Claims 2-4, 6-10, 12-14, and 16-26 are rejected under an obviousness-type provisional nonstatutory double patenting based on their dependence on their respective independent/base Claims 1 and 11.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The present rejection(s) reference specific passages from cited prior art. However, Applicant is advised that the rejections are based on the entirety of each cited prior art. That is, each cited prior art reference “must be considered in its entirety”. Therefore, Applicant is advised to review all portions of the cited prior art if traversing a rejection based on the cited prior art.
Claims 1-2, 4, 6-8, 11-12, 14, 16-18, 21-22, and 24-26 are rejected under 35 U.S.C. 103 as being unpatentable over Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) in view of Zemlok et al. (US PGPUB 2018/0153634 – “Zemlok”).
Regarding Claim 1, Gormley discloses:
A method of controlling an endoscopic device (Gormley FIG. 1A, catheter tube 100), the method comprising:
acquiring an image of a lower gastrointestinal tract (Gormley FIG. 11, showing articulated stylet 1118 passing through a lower colon) from an image sensor (Gormley paragraph [0134], “The distal end 1112 of the articulated stylet 1118 may be located at the target location, and may include an imaging device“);
acquiring environment information with respect to a front-end portion of the endoscopic device, wherein the environment information includes structural information with respect to a body shape that characterizes a three-dimensional shape of a lumen of the lower gastrointestinal tract (Gormley FIG. 11, articulated stylus 1118 having an imaging device – see Gormley paragraph [0134], passing through a lower gastrointestinal tract);
detecting at least one first body part from the image, based on a pre-trained model (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time, a deep-learning detector configured to identify orifices and structures within the enteral cavity or respiratory tract, the deep-learning detector including at least one convolutional-neural-network-based detection algorithm that is trained to learn unified hierarchical representations, that identifies the orifices and structures based on the captured image data, and that calculates the navigation data based on the captured image data and the target destination”);
calculating relative position information between the at least one first body part and the front-end portion of the endoscopic device; generating, based on the relative position information, a first control signal for steering the front-end portion to correspond to the at least one first body part, and wherein generating the first control signal comprises determining a steering direction and a steering magnitude that conforms to the three-dimensional shape of the lumen (Gormley FIG. 11, showing articulated stylet 1118 passing through a lower gastrointestinal tract; Gormley paragraph [0094], “The imaging device 108 may capture image data (“captured image data”) corresponding to structures (e.g., of the organ being traversed by the catheter tube 100) surrounding the distal end of the catheter tube 100. For example, LiDAR, time of flight imaging, visual image sensing (e.g., which may involve the capture of still images and/or video), or other applicable imaging techniques may be applied to capture the image data. Topographic image data that may be included in the captured image data may provide information related to the shape, volume, consistency, and location of the organ, or the portion of the organ, through which the distal end of the catheter tube 100 is traversing. The captured image data may be transmitted to and used by one or more artificial intelligence (AI) models executed by the remote device that is in wireless electronic communication with the transceiver 106, providing feedback to the AI model(s) regarding the location and position of the catheter tube 100 in the subject's body (e.g., in an organ thereof). Thus, the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100 and to continuously monitor the location of the catheter tube 100 once it has reached the target location”); and
transmitting the first control signal to a driver (Gormley FIG. 8A, rotational motor 801 connected to stylet 804; Gormley paragraph [0144], ”the stylet of the robot extending from the RCDC would be placed through one end of the endotracheal tube to be inserted and brought out the other end…Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure…and through the use of the actuators and motors that control all of its degrees of freedom, steer the stylet…This will all be done using computer vision as a guide, without input required from any clinician at the patient's side. The decisions guiding the direction of the stylet will all be automated through the computer algorithm and controlled through the mechanical system of the device.”);
identifying at least one second body part from the image based on the pre-trained model; calculating relative pose information between the identified at least one second body part and the front-end portion, the relative pose information representing a change in pose of the front-end portion from a first pose to a second pose; generating, based on the relative pose information, a second control signal, distinct from the first control signal, for positioning the front-end portion at a pose suitable for photographing the identified at least one second body part; and transmitting the second control signal to the drive (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time, a deep-learning detector configured to identify orifices and structures within the enteral cavity or respiratory tract”; Gormley paragraph [0093], “transceiver 106 may also wirelessly transmit imaging data (e.g., topographic image data, still image data, and/or video data) captured by the imaging device 108 to the remote device. The transceiver 106 may transmit this data to the remote device both during the device placement process (e.g., as the catheter tube 100 is automatically driven to a target location)”; Gormley paragraph [0094], “the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100”; Gormley paragraph [0144], “Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure in the nasopharynx or oropharynx (depending on the site of insertion) and given these images the robot would direct the stylet down the pharynx into the larynx. At this point the epiglottis will come into the sight of the robot, which will be recognized. The algorithm will recognize the juncture of the larynx anteriorly and the esophagus posteriorly and through the use of the actuators and motors that control all of its degrees of freedom”; Examiner interprets this continuous capturing of images of interim landmarks while traversing to the target during the automatic drive of the catheter tube disclosed by Gormley as disclosing the presently claimed steps of 1) identifying an interim second body part from the image based on the pre-trained model and 2) adjusting the movement of the endoscope by use of this interim second body part image).
Gormley does not explicitly disclose acquiring environment information with respect to a front-end portion of the endoscopic device, and using the environment information when generating the first control signal and second control signal.
Zemlok teaches acquiring environment information with respect to a front-end portion of the endoscopic device, and using the environment information when generating the first control signal and second control signal (Zemlok FIG. 2B, driver motor M and endoscope 200; Zemlok paragraph [0034], “control device 4 may control the operation of a rotation motor, such as, for example, a canister motor “M” (FIG. 2B)…configured to drive a relative rotation of motor assembly 410 of IDU 400 and in turn adapter assembly 120 and endoscope 200”; Examiner notes that the term “environment information” is used in paragraph [0096] of the present specification as representing spatial position and/or rotation angle. As such, Zemlok teaches rotating the endoscope from a starting environment (rotation angle X) to a new environment (rotation angle Y)).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Zemlok’s use of rotational information (environment information) with the method disclosed by Gormley. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of an endoscope control method that accounts for passageways having shapes that require rotation of the endoscope as the endoscope passes through the passageways.
Regarding Claim 2, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Zemlok further teaches wherein the acquiring of the environment information comprises: calculating rotation information based on an encoder value of the driver; and calculating position information based on the rotation information (Zemlok paragraph [0034], “control device 4 may control the operation of a rotation motor, such as, for example, a canister motor “M” (FIG. 2B)…configured to drive a relative rotation of motor assembly 410 of IDU 400 and in turn adapter assembly 120 and endoscope 200”; Examiner interprets known rotation of Zemlok’s motor “M” results in knowing/calculating the position of the front-end portion of the endoscope device).
Gormley further discloses calculating position information based on the acquired image (Gormley paragraph [0038], “The system may therefore enable directed placement and immediate confirmation of correct positioning of the tube using topographic imaging data captured by one or more image sensors of the system and corresponding to the cavity in which the tube is positioned.”)
Regarding Claim 4, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley further discloses wherein the acquiring of the image of the upper gastrointestinal tract comprises: acquiring a first image at a first point; and acquiring a second image at a second point, and the calculating of the relative position information comprises calculating a target rotation angle of the front-end portion of the endoscopic device based on i) an angle change of the front-end portion of the endoscopic device between the first point and the second point and ii) a change between the first image and the second image (Gormley paragraph [0093], “transceiver 106 may also wirelessly transmit imaging data (e.g., topographic image data, still image data, and/or video data) captured by the imaging device 108 to the remote device. The transceiver 106 may transmit this data to the remote device both during the device placement process (e.g., as the catheter tube 100 is automatically driven to a target location)”; Gormley paragraph [0094], “the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100”; Gormley paragraph [0144], “Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure in the nasopharynx or oropharynx (depending on the site of insertion) and given these images the robot would direct the stylet down the pharynx into the larynx. At this point the epiglottis will come into the sight of the robot, which will be recognized. The algorithm will recognize the juncture of the larynx anteriorly and the esophagus posteriorly and through the use of the actuators and motors that control all of its degrees of freedom”; Examiner interprets this continuous endoscopic angle change and changes to captured images during the automatic drive of the catheter tube disclosed by Gormley as disclosing the presently claimed steps of 1) acquiring multiple images while traversing through the patient, and 2) adjusting the movement of the endoscope by use of calculated rotation angle and passing landmarks shown in the images).
Regarding Claim 6, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley further discloses wherein the pre-trained model comprises a classification model and a detection model both trained by using, as a data set, an image labelled with respect to the at least one first body part and the at least one second body part with respect to the upper gastrointestinal tract (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time, a deep-learning detector configured to identify orifices and structures within the enteral cavity or respiratory tract, the deep-learning detector including at least one convolutional-neural-network-based detection algorithm that is trained to learn unified hierarchical representations, that identifies the orifices and structures based on the captured image data, and that calculates the navigation data based on the captured image data and the target destination, and a median-flow filtering based visual tracking module configured to predict the motion vector of the articulated stylet using sparse optical flow.”; Gormley paragraph [0168], “The training part was implemented by feeding the annotated image to Keras implementation of YOLOv3. The version for Keras was 2.2.4 and this version runs TensorFlow 1.15 on the backend. The dataset was created with an annotation software, VoTT R (Microsoft, Redmond, Wash.).”; See also highlighted portions of in the appendix provided herein, which describe VOTT labeling images for classification and detection.).
Regarding Claim 7, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley further discloses wherein the generating of the second control signal comprises: identifying at least one photographing point corresponding to the identified at least one second body part; generating, based on the at least one photographing point and the relative pose information, the second control signal for controlling rotation of the front-end portion (see paragraphs [0093] – [0094] and [0144] of Gormley, as cited in the rejection of Claim 4, which describe continuous/repetitive photography of body parts used to control rotation of an endoscope).
Regarding Claim 8, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley further discloses photographing an image when a position of the front-end portion corresponds to the at least one photographing point (see paragraphs [0093] – [0094] and [0144] of Gormley, as cited in the rejection of Claim 4, that describe continuous/repetitive photography of body parts).
Regarding Claim 11, Gormley discloses:
An endoscopic device (Gormley FIG. 11, articulated stylet 1118) comprising:
a front-end portion comprising an image sensor to acquire an image of a lower gastrointestinal tract (Gormley FIG. 11, showing articulated stylet 1118 passing through a lower colon; Gormley paragraph [0134], “The distal end 1112 of the articulated stylet 1118 may be located at the target location, and may include an imaging device“) ;
a driver configured to control a rotation angle of the front-end portion (Gormley FIG. 4A, robotic control and display center (RCDC) 400; Gormley paragraph [0144], ”the stylet of the robot extending from the RCDC would be placed through one end of the endotracheal tube to be inserted and brought out the other end…through the use of the actuators and motors that control all of its degrees of freedom, steer the stylet…This will all be done using computer vision as a guide, without input required from any clinician at the patient's side. The decisions guiding the direction of the stylet will all be automated through the computer algorithm and controlled through the mechanical system of the device.”); and
a controller (Gormley FIG. 4A, controller 406; Gormley paragraph [0101], “controller 406 (e.g., which may include one or more computer processors)”) configured to:
acquire the image of the lower gastrointestinal tract (Gormley FIG. 11, showing articulated stylet 1118 passing through a lower colon) from an image sensor (Gormley paragraph [0134], “The distal end 1112 of the articulated stylet 1118 may be located at the target location, and may include an imaging device“);
acquire environment information with respect to the front-end portion, wherein the environment information includes structural information with respect to a body shape that characterizes a three-dimensional shape of a lumen of the lower gastrointestinal tract (Gormley FIG. 11, showing articulated stylet 1118 with an imaging device traversing through rectum1104 and colons 1106, 1108, 1110, 1114);
detect, based on a pre-trained model, at least one first body part from the image (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time, a deep-learning detector configured to identify orifices and structures within the enteral cavity or respiratory tract, the deep-learning detector including at least one convolutional-neural-network-based detection algorithm that is trained to learn unified hierarchical representations, that identifies the orifices and structures based on the captured image data, and that calculates the navigation data based on the captured image data and the target destination”);
calculate relative position information between the at least one first body part and the front-end portion of the endoscopic device; generate, based on the environment information and the relative position information, a first control signal to steer the front-end portion to correspond to the at least one first body part (Gormley paragraph [0094], “The imaging device 108 may capture image data (“captured image data”) corresponding to structures (e.g., of the organ being traversed by the catheter tube 100) surrounding the distal end of the catheter tube 100. For example, LiDAR, time of flight imaging, visual image sensing (e.g., which may involve the capture of still images and/or video), or other applicable imaging techniques may be applied to capture the image data. Topographic image data that may be included in the captured image data may provide information related to the shape, volume, consistency, and location of the organ, or the portion of the organ, through which the distal end of the catheter tube 100 is traversing. The captured image data may be transmitted to and used by one or more artificial intelligence (AI) models executed by the remote device that is in wireless electronic communication with the transceiver 106, providing feedback to the AI model(s) regarding the location and position of the catheter tube 100 in the subject's body (e.g., in an organ thereof), wherein the first control signal specifies a steering direction and a steering magnitude that conform to the three-dimensional shape of the lumen (Gormley FIG. 11 showing image capturing stylet 1118 traversing through a lower gastrointestinal system). Thus, the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100 and to continuously monitor the location of the catheter tube 100 once it has reached the target location”);
transmit the first control signal to the driver (Gormley FIG. 8A, rotational motor 801 connected to stylet 804; Gormley paragraph [0144], ” the stylet of the robot extending from the RCDC…Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure …and through the use of the actuators and motors that control all of its degrees of freedom, steer the stylet…This will all be done using computer vision as a guide, without input required from any clinician at the patient's side. The decisions guiding the direction of the stylet will all be automated through the computer algorithm and controlled through the mechanical system of the device.”);
identify at least one second body part from the image based on the pre-trained model; calculating relative pose information between the identified at least one second body part and the front-end portion, the relative pose information representing a change in pose of the front-end portion from a first pose to a second pose; generate, based on the relative pose information, a second control signal, distinct from the first control signal, for positioning the front-end portion at a pose suitable for photographing the identified at least one second body part; and transmit the second control signal to the drive (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time, a deep-learning detector configured to identify orifices and structures within the enteral cavity or respiratory tract”; Gormley paragraph [0093], “transceiver 106 may also wirelessly transmit imaging data (e.g., topographic image data, still image data, and/or video data) captured by the imaging device 108 to the remote device. The transceiver 106 may transmit this data to the remote device both during the device placement process (e.g., as the catheter tube 100 is automatically driven to a target location)”; Gormley paragraph [0094], “the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100”; Gormley paragraph [0144], “Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure in the nasopharynx or oropharynx (depending on the site of insertion) and given these images the robot would direct the stylet down the pharynx into the larynx. At this point the epiglottis will come into the sight of the robot, which will be recognized. The algorithm will recognize the juncture of the larynx anteriorly and the esophagus posteriorly and through the use of the actuators and motors that control all of its degrees of freedom”; Examiner interprets this continuous capturing of images of interim landmarks while traversing to the target during the automatic drive of the catheter tube disclosed by Gormley as disclosing the presently claimed steps of 1) identifying an interim second body part from the image based on the pre-trained model and 2) adjusting the movement of the endoscope by use of this interim second body part image).
Gormley does not explicitly disclose acquiring environment information with respect to a front-end portion of the endoscopic device, and using the environment information when generating the first control signal and second control signal.
Zemlok teaches acquiring environment information with respect to a front-end portion of the endoscopic device, and using the environment information when generating the first control signal and the second control signal (Zemlok FIG. 2B, driver motor M and endoscope 200; Zemlok paragraph [0034], “control device 4 may control the operation of a rotation motor, such as, for example, a canister motor “M” (FIG. 2B)…configured to drive a relative rotation of motor assembly 410 of IDU 400 and in turn adapter assembly 120 and endoscope 200”; Examiner notes that the term “environment information” is used in paragraph [0096] of the present specification as representing spatial position and/or rotation angle. As such, Zemlok teaches rotating the endoscope from a starting environment (rotation angle X) to a new environment (rotation angle Y)).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Zemlok’s use of rotational information (environment information) with the method disclosed by Gormley. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of an endoscope control method that accounts for passageways having shapes that require rotation of the endoscope as the endoscope passes through the passageways.
Regarding Claim 12, Gormley in view of Zemlok teaches the features of Claim 11, as described above.
Zemlok further teaches wherein the controller is further configured to calculate rotation information based on an encoder value of the driver and calculate position information based on the rotation information (Zemlok paragraph [0034], “control device 4 may control the operation of a rotation motor, such as, for example, a canister motor “M” (FIG. 2B)…configured to drive a relative rotation of motor assembly 410 of IDU 400 and in turn adapter assembly 120 and endoscope 200”; Examiner interprets known rotation of Zemlok’s motor “M” results in knowing/calculating the position of the front-end portion of the endoscope device).
Gormley further discloses wherein the controller is configured to calculate position information based on the acquired image (Gormley paragraph [0038], “The system may therefore enable directed placement and immediate confirmation of correct positioning of the tube using topographic imaging data captured by one or more image sensors of the system and corresponding to the cavity in which the tube is positioned.”).
Regarding Claim 14, Gormley in view of Zemlok teaches the features of Claim 11, as described above.
Gormley further discloses
wherein the front-end portion further comprises an illuminator (Gormley FIG. 2, light source 220 in distal end of endoscope 100/200), and
the controller is further configured to acquire a first image at a first point and a second image at a second point and calculate, based on i) an angle change of the front-end portion between the first point and the second point and ii) a change between the first image and the second image, a target rotation angle of the front-end portion (Gormley paragraph [0093], “transceiver 106 may also wirelessly transmit imaging data (e.g., topographic image data, still image data, and/or video data) captured by the imaging device 108 to the remote device. The transceiver 106 may transmit this data to the remote device both during the device placement process (e.g., as the catheter tube 100 is automatically driven to a target location)”; Gormley paragraph [0094], “the image data generated by the imaging device 108 may be used to guide the placement of the catheter tube 100”; Gormley paragraph [0144], “Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure in the nasopharynx or oropharynx (depending on the site of insertion) and given these images the robot would direct the stylet down the pharynx into the larynx. At this point the epiglottis will come into the sight of the robot, which will be recognized. The algorithm will recognize the juncture of the larynx anteriorly and the esophagus posteriorly and through the use of the actuators and motors that control all of its degrees of freedom”; Examiner interprets this continuous endoscopic angle change and changes to captured images during the automatic drive of the catheter tube disclosed by Gormley as disclosing the presently claimed steps of 1) acquiring multiple images while traversing through the patient, and 2) adjusting the movement of the endoscope by use of calculated rotation angle and passing landmarks shown in the images).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to utilize Gormley’s system for recognizing structure in the nasopharynx or oropharynx with the endoscopic device taught by Gormley and Zemlok . A person having ordinary skill in the art would be motivated to combine these
prior art elements according to known methods to yield the predictable result of an endoscope device that is able to identify structures in any area of an alimentary canal.
Regarding Claim 16, Gormley in view of Zemlok teaches the features of Claim 11, as described above.
Gormley further discloses wherein the pre-trained model comprises a classification model and a detection model both trained by using, as a data set, an image labelled with respect to the at least one first body part and the at least one second body part with respect to the lower gastrointestinal tract (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time, a deep-learning detector configured to identify orifices and structures within the enteral cavity or respiratory tract, the deep-learning detector including at least one convolutional-neural-network-based detection algorithm that is trained to learn unified hierarchical representations, that identifies the orifices and structures based on the captured image data, and that calculates the navigation data based on the captured image data and the target destination, and a median-flow filtering based visual tracking module configured to predict the motion vector of the articulated stylet using sparse optical flow.”; Gormley paragraph [0168], “The training part was implemented by feeding the annotated image to Keras implementation of YOLOv3. The version for Keras was 2.2.4 and this version runs TensorFlow 1.15 on the backend. The dataset was created with an annotation software, VoTT R (Microsoft, Redmond, Wash.).”; See also highlighted portions of in the appendix provided herein, which describe VOTT labeling images for classification and detection.)..
Regarding Claim 17, Gormley in view of Zemlok teaches the features of Claim 11, as described above.
Gormley further discloses wherein the controller is further configured to identify at least one photographing point corresponding to the identified at least one second body part and generate, based on the at least one photographing point and the relative pose information, a second control signal for controlling rotation of the front-end portion (see paragraphs [0093] – [0094] and [0144] of Gormley, cited above in the rejection of Claim 14, which describe continuous/repetitive photography of body parts used to control rotation of an endoscope).
Regarding Claim 18, Gormley in view of Zemlok teaches the features of Claim 17, as described above.
Gormley further discloses wherein the controller is further configured to photograph an image, when a position of the front-end portion corresponds to the at least one photographing point (see paragraphs [0093] – [0094] and [0144] of Gormley, cited above in the rejection of Claim 14, which describe continuous/repetitive photography of body parts).
Regarding Claim 21, Gormley in view of Zemlok teaches the features of Claim 1 as described above.
Gormley in view of Zemlok does not explicitly teach wherein acquiring the environment information comprises generating a three-dimensional body-shape structure of the lower gastrointestinal tract using simultaneous localization and mapping (SLAM) based on feature points extracted from a plurality of acquired images.
Rivlin teaches wherein acquiring the environment information comprises generating a three-dimensional body-shape structure of the lower gastrointestinal tract using simultaneous localization and mapping (SLAM) based on feature points extracted from a plurality of acquired images (Rivlin FIG. 2, medical imaging system 202 and clinical support system 204; Rivlin paragraph [0061], “clinical support system 204 can perform simultaneous localization and mapping (SLAM) using the video data stream obtained from the medical imaging system 202 during the gastroenterological procedure. Using SLAM, the clinical support system 204 can generate and/or update a three-dimensional model of portions of the anatomical structure (e.g., colon, small intestine, stomach, other internal organ, etc.) of the patient viewed by the camera”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Rivlin’s SLAM modeling with the method taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a 3D model generated from images of a gastrointestinal (GI) tract, in order to identify not only a normal structure of the GI tract, but also any abnormalities such as polyps, lesions, tumors, etc. (see Rivlin paragraph [0061]).
Regarding Claim 22, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley further discloses wherein the relative pose information comprises both position information and orientation information of the front-end portion with respect to the identified at least one second body part (Gormley paragraph [0144], “Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure in the nasopharynx or oropharynx (depending on the site of insertion) and given these images the robot would direct the stylet down the pharynx into the larynx. At this point the epiglottis will come into the sight of the robot, which will be recognized.”; Examiner interprets this continuous capturing of images of interim landmarks while traversing to the target teaches the claimed feature in Claim 22 of identifying a pose of an endoscope based an interim second body part seen in a captured image.).
Regarding Claim 24, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley discloses wherein transmitting the second control signal to the driver causes the driver to control the front-end portion to achieve the pose suitable for photographing (Gormley paragraph [0054], “at least one artificial intelligence model may include a detection and tracking model that processes the captured image data in near-real time…and that calculates the navigation data based on the captured image data and the target destination”).
Gormley further discloses controlling at least one of a rotation angle or a curvature of the front-end portion of the endoscope (Gormley paragraph [0111], “A transmission may be included in the robotic control engine 424, which may be used to enable automatic rotation and articulation of the catheter”).
Regarding Claim 25, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Zemlok further teaches wherein the environment information includes: a spatial position of the front-end portion, or information including directionality of the front-end portion (Zemlok FIG. 2B, driver motor M and endoscope 200; Zemlok paragraph [0034], “control device 4 may control the operation of a rotation motor, such as, for example, a canister motor “M” (FIG. 2B)…configured to drive a relative rotation of motor assembly 410 of IDU 400 and in turn adapter assembly 120 and endoscope 200”; Examiner notes that the term “environment information” is used in paragraph [0096] of the present specification as representing spatial position and/or rotation angle. As such, Zemlok teaches rotating the endoscope from a starting environment (rotation angle X) to a new environment (rotation angle Y)).
Regarding Claim 26, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley further discloses: wherein determining the steering direction and the steering magnitude comprises: determining the steering direction and the steering magnitude based on a three-dimensional shape of a lumen, and steering the front-end portion along a path defined by the three-dimensional shape of the lumen such that the front-end portion follows the lumen (Gormley FIG. 11, showing articulated stylet 1118 passing through a lower gastrointestinal tract; Gormley paragraph [0144], “Gormley paragraph [0144], ”the stylet of the robot extending from the RCDC would be placed through one end of the endotracheal tube to be inserted and brought out the other end…Using images obtained from the visual and topographic cameras at the tip of the stylet, the computer's algorithm would begin to recognize structure…and through the use of the actuators and motors that control all of its degrees of freedom, steer the stylet…This will all be done using computer vision as a guide, without input required from any clinician at the patient's side”).
Claims 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) in view of Zemlok et al. (US PGPUB 2018/0153634 – “Zemlok”) and Verma et al. (US PGPUB 2022/0086412 – “Verma”).
Regarding Claim 3, Gormley in view of Zemlok teaches the features of Claim 2, as described above.
Gormley in view of Zemlok does not explicitly teach generating a stitched image based on a feature point of the acquired image; and generating a body shape structure based on the stitched image.
Verma teaches generating a stitched image based on a feature point of the acquired image; and generating a body shape structure based on the stitched image (Verma FIG. 3, image processing system 340; Verma paragraph [0038], “image processing software component 340 captures multiple images per video frame and generates a composite image based on those images”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Verma’s composite image generation with the method taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a method of image recognition used in endoscopic control that is faster (see Verma paragraph [0038]).
Regarding Claim 13, Gormley in view of Zemlok teaches the features of Claim 12, as described above.
Gormley in view of Zemlok does not explicitly teach wherein the controller is further configured to generate a stitched image based on a feature point of the acquired image and generate a body shape structure based on the stitched image.
Verma teaches wherein the controller is further configured to generate a stitched image based on a feature point of the acquired image and generate a body shape structure based on the stitched image (Verma FIG. 3, image processing system 340; Verma paragraph [0038], “image processing software component 340 captures multiple images per video frame and generates a composite image based on those images”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Verma’s composite image generation with the endoscopic device taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a method of image recognition used in endoscopic control that is faster (see Verma paragraph [0038]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) in view of Zemlok et al. (US PGPUB 2018/0153634 – “Zemlok”) and Uchiyama (US PGPUB 2008/0139883 – “Uchiyama”).
Regarding Claim 9, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley in view of Zemlok does not explicitly teach displaying the environment information on a display.
Uchiyama teaches displaying the environment information on a display (Uchiyama FIG. 5, endoscope 20; Uchiyama FIG. 1, rotation-magnetic-field control circuit 73, display device 80; endoscope 20 Uchiyama paragraph [0105], “Direction-of-movement instructions for the capsule endoscope 20, which the operator inputs from the input device 74, are input to the rotation-magnetic-field control circuit 73, together with data from the position detection apparatus 50 indicating the direction in which the capsule endoscope 20 is currently pointing (the direction of a rotation axis (longitudinal axis) R of the capsule endoscope 20). Then, signals for controlling the Helmholtz coil drivers 72X, 72Y, and 72Z are output from the rotation-magnetic-field control circuit 73, and rotational phase data of the capsule endoscope 20 is output to the image display device 80”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Uchiyama’s step of displaying rotational phase data of a capsule on an image display device with the method taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a method that shows in real-time the rotational phase of an endoscope, in order to provide the user of the endoscope with orientation data in order to understand the orientation of a target area of interest during an endoscopic procedure.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) in view of Zemlok et al. (US PGPUB 2018/0153634 – “Zemlok”) and Rabindran et al. (US PGPUB 2019/0143506 – “Rabindran”).
Regarding Claim 10, Gormley in view of Zemlok teaches the features of Claim 1, as described above.
Gormley in view of Zemlok does not explicitly teach generating torque feedback and transmitting the torque feedback to a manipulator.
Rabindran teaches generating torque feedback and transmitting the torque feedback to a manipulator via the driver (Rabindran FIG. 1A, control system 20, medical tool 14, manipulator assembly 12; Rabindran paragraph [0043], “control system 20 may include one or more servo controllers that receive force and/or torque feedback from the medical tool 14 or from the manipulator assembly 12. Responsive to the feedback, the servo controllers transmit signals to the operator input system 16. The servo controller(s) may also transmit signals that instruct the manipulator assembly 12 to move the medical tool(s) 14 and/or 15 which extends into an internal procedure site within the patient body via openings in the body.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the use of Rabindran’s torque feedback with the method taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a method capable of local/autonomous control of movement of an endoscope (see Rabindran paragraph [0043], “the controller and manipulator assembly are provided as part of an integrated system such as a teleoperational arm cart positioned proximate to the patient's body during the medical procedure”).
Claims 19 and 23 are rejected under 35 U.S.C. 103 as being unpatentable Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) in view of Zemlok et al. (US PGPUB 2018/0153634 – “Zemlok”) and Kowshik et al. (US PGPUB 2014/0051987 – “Kowshik”).
Regarding Claim 19, Gormley in view of Zemlok teaches the features of Claim 11, as described above.
Gormley further discloses a display (Gormley FIG. 4A, display 414)
Gormley in view of Zemlok does not explicitly teach wherein the controller is further configured to display the environmental information on the display.
Kowshik teaches wherein the controller is further configured to display environmental information on the display (Kowshik FIG. 1, display system 111 and control system 116; Kowshik paragraph [0026], “display system 111 may display an image of the surgical site and surgical instruments captured by the visualization system 110”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Kowshik’s imaging of instruments in situ with the endoscopic device taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of an endoscope system that is tracked in real-time during an endoscopic operation, in order to control the position of the endoscopic (see Kowshik paragraph [0025]).
Regarding Claim 23, Gormley in view of Zemlok teaches the features of Claim 22, as described above.
Gormley in view of Zemlok does not explicitly teach wherein the orientation information comprises directional information including at least one of a pitch angle, a yaw angle, or a roll angle of the front-end portion.
Kowshik teaches wherein the orientation information comprises directional information including at least one of a pitch angle, a yaw angle, or a roll angle of the front-end portion (Kowshik FIG. 3a, sensor component 268 within probe assembly 250; Kowshik paragraph [0054], “sensor component 268 can be an electromagnetic (EM) sensor component…the EM sensor system may be configured and positioned to measure six degrees of freedom, e.g., three position coordinates X, Y, Z and three orientation angles indicating pitch, yaw, and roll of a base point”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the use of Kowshik’s three-axis sensor with the method taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of an endoscope device control method that manipulates the endoscope device in pitch/yaw/roll angles, in order to move a GI tract through six degrees of freedom.
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) in view of Zemlok et al. (US PGPUB 2018/0153634 – “Zemlok”), Ono et al. (US PGPUB 2014/0203170 – “Ono”), and Rabindran et al. (US PGPUB 2019/0143506 – “Rabindran”).
Regarding Claim 20, Gormley in view of Zemlok teaches the features of Claim 11, as described above.
Gormley in view of Zemlok does not explicitly teach:
a manipulator including a curved steering portion,
wherein the controller is further configured to generate torque feedback based on the driver and transmit the torque feedback to the curved steering portion.
Ono teaches a manipulator (Ono FIG. 1, operation unit 22) including a curved steering portion (Ono FIG. 1, curving knob 221 having a curved shape).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine Ono’s curving knob with the endoscope device taught by Gormley in view of Zemlok. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of an endoscope having a proximal controller that is easy for a user to feel and control without looking, based on the distinct/rounded shape of the controller.
Gormley in view of Zemlok and Ono does not explicitly teach wherein the controller is further configured to generate torque feedback and transmit the torque feedback to the curved steering portion via the driver.
Rabindran teaches wherein the controller is further configured to generate torque feedback and transmit the torque feedback to the curved steering portion via the driver (Rabindran FIG. 1A, control system 20, medical tool 14, manipulator assembly 12; Rabindran paragraph [0043], “control system 20 may include one or more servo controllers that receive force and/or torque feedback from the medical tool 14 or from the manipulator assembly 12. Responsive to the feedback, the servo controllers transmit signals to the operator input system 16. The servo controller(s) may also transmit signals that instruct the manipulator assembly 12 to move the medical tool(s) 14 and/or 15 which extends into an internal procedure site within the patient body via openings in the body.”).
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the use of Rabindran’s torque feedback with the endoscope device taught by Gormley in view of Zemlok and Ono. A person having ordinary skill in the art would be motivated to combine these prior art elements according to known methods to yield the predictable result of a method capable of local/autonomous control of movement of an endoscope (see Rabindran paragraph [0043], “the controller and manipulator assembly are provided as part of an integrated system such as a teleoperational arm cart positioned proximate to the patient's body during the medical procedure”).
Response to Arguments
Applicant's arguments filed March 31, 2026 regarding the provisional rejection of Claims 1 and 11 on the ground of obviousness-type nonstatutory double patenting as being unpatentable over respective Claims 1 and 11 of copending Application No. 18/585,449 in view of Gormley et al. (US PGPUB 2021/0059607 – “Gormley”) have been fully considered but they are not persuasive. On pages 11-12 of the March 31, 2026 amendment, Applicant asserts that the new features made to Claims 1 and 11 overcome this rejection. However, Claims 1 and 11 of copending Application No. 18/585,449 were also amended on March 31, 2026, such that the rejection is maintained, as described above. As such, the double-patenting rejection of Claims 1-4, 6-14, and 16-26 is maintained.
Applicant's arguments filed March 31, 2026 regarding the rejection of Claims 1 and 11 under 35 U.S.C. 103 have been fully considered but they are not persuasive.
On page 10, Applicant first asserts that the cited prior art, and specifically Gormley et al. (US PGPUB 2021/0059607 – “Gormley”), fails to teach or suggest the newly-cited features of:
acquiring environment information with respect to a front-end portion of the endoscopic device, wherein the environment information includes structural information with respect to a body shape that characterizes a three-dimensional shape of a lumen of the lower gastrointestinal tract;
generating, based on the environment information and the relative position information, a first control signal for steering the front-end portion by determining a steering direction and a steering magnitude that conforms to the three- dimensional shape of the lumen; and
identifying at least one second body part from the image, based on the pre-trained model; calculating relative pose information between the identified at least one second body part and the front-end portion, the relative pose information representing a change in pose of the front-end portion from a first pose to a second pose; generating, based on the relative pose information, a second control signal, distinct from the first control signal, for positioning the front-end portion at a pose suitable for photographing the identified at least one second body part; and then transmitting the second control signal to the driver.
Examiner notes that most of the underlined features are from original Claim 5. The reasoning for rejecting those features are found both in the December 17, 2025 non-final rejection, as well as the present rejection presented above in the rejection of Claims 1 and 11 under 35 U.S.C. 103. Applicant is referred to Examiner’s reasoning for making those rejections, which are incorporated by reference in this response to the amendments.
The feature that was not previously rejected, and which is the focus of pages 10-11 of the March 31, 2026 response, relate to steering through a three-dimensional shape of a lumen of the lower gastrointestinal tract. However, as cited in the 35 U.S.C. 103 rejection of Claims 1 and 11, this feature is disclosed by Gormley FIG. 11 and the cited passages from the written description of Gormley, including but not limited to Gormley paragraph [0134], which describe a stylet navigating through a lower gastrointestinal tract.
As such, the rejection of independent Claims 1 and 11, as well as dependent Claims 2-4, 6-10, 12-14, and 16-26 under 35 U.S.C. 103 is maintained.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIM BOICE whose telephone number is (571)272-6565. The examiner can normally be reached Monday-Friday 9:00am - 5:00pm Eastern.
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JIM BOICE
Examiner
Art Unit 3795
/JAMES EDWARD BOICE/Examiner, Art Unit 3795
/ANH TUAN T NGUYEN/Supervisory Patent Examiner, Art Unit 3795
5/4/26
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