DETAILED ACTION
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 .
Specification
The disclosure is objected to because of the following informalities:
The abstract is greater than 150 words. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length. See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the BRI of “one or more storage media storing instructions thereon” can encompass non-statutory transitory forms of signal transmission, such as a propagating electrical or electromagnetic signal per se. See In re Nuijten, 500 F.3d 1346, 84 USPQ2d 1495 (Fed. Cir. 2007) and MPEP 2106.03.II. The description does not entirely limit the medium as non-transitory, see at least [0094] (“Alternatively or in addition, the program instructions can be encoded on an artificially generated propagated signal, e.g., a machine-generated electrical, optical, or electromagnetic signal that is generated to encode information for transmission to suitable receiver apparatus for execution by a data processing apparatus.”). The examiner suggests adding non-transitory language to claims 19 and 20 to overcome the rejection.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 9, 12, and 19 is/are rejected under 35 U.S.C. 102(a)(1) and (a)(2) as being anticipated by Graetzel (US 20200046434 A1).
Regarding Claim 1,
Graetzel teaches
A system, comprising: one or more processors, coupled with memory, to: (“The functions described herein may be stored as one or more instructions on a processor-readable or computer-readable medium. The term “computer-readable medium” refers to any available medium that can be accessed by a computer or processor.” See at least [0149]; “A non-transitory computer readable storage medium having stored thereon instructions that, when executed, cause a processor of a device to at least:” See at least claim 12)
receive one or more image frames captured via a camera for a medical session with a robotic medical system; (“accessing image data captured by an imaging device located proximal to a tip of the instrument,” See at least [0010]; “The endoscope 118 is a tubular and flexible surgical instrument that is inserted into the anatomy of a patient to capture images of the anatomy (e.g., body tissue). In particular, the endoscope 118 includes one or more imaging devices (e.g., cameras or other types of optical sensors) that capture the images.” See at least [0040]; “Image data may include one or more image frames captured by the imaging device at the instrument tip, as well as information such as frame rates or timestamps.” See at least [0085])
determine, based at least in part on the one or more image frames, a visual geometry of an instrument configured to perform a procedure via the robotic medical system during at least a portion of the medical session; (“the shape data comparison module 907 may determine, based on the image data received from the image data store 910, an expected orientation of the instrument (e.g., at or near the distal end of the instrument).” See at least [0115]; “fluoroscopy (X-ray) images can be analyzed by a computer vision algorithm to extract the silhouette of the instrument” See at least [0118])
determine, based at least in part on data received from a sensor of a motor of the robotic medical system, a sensed geometry of the instrument; (“FIG. 4D, the system may determine, based on the robotic data, one or more conditions that the endoscope 118 is expected to satisfy (e.g., the curvature value at a given point along the endoscope 118 should be within a predetermined range of values, or should be within a range of values determined based on the pull force on the pull wires and/or the distances that the pull wires have been actuated) … as shown in FIG. 4D, the system may determine, based on the robotic data (e.g., pull force and distances), the robotic-data-based shape prediction 473 exhibiting the predicted curvature 477 at a given point.” See at least [0069]; See at least [0087]; Also see at least figs. 3A and 3B; Examiner Interpretation: At least the sensor that detects pull force on the wires is the sensor of the motor.)
and provide, based at least in part on a comparison of the visual geometry with the sensed geometry, a notification of a state of the instrument during the medical session. (“The shape data comparison module 907 may then determine whether the shape data is inconsistent with the expected orientation of the instrument (e.g., the image data indicates that the tip of the instrument is pointing in a direction parallel to the anatomical lumen, but the shape data indicates that the tip of the instrument is pointing at an inner wall of the anatomical lumen).” See at least [0115]; “the shape data comparison module 907 may then determine whether the shape data is inconsistent with the extracted silhouette of the instrument.” See at least [0118]; “the shape data comparison module 907 determines that a mismatch between the shape data and the robotic data has been detected for over a threshold amount of time, and outputs an alert indicating that the instrument may be damaged.” See at least [0120])
Regarding Claim 9,
Graetzel further teaches
wherein the one or more processors are further configured to: periodically or continuously determine the visual geometry, determine the sensed geometry, and provide the notification of the state of the instrument during the medical session. (“the shape data comparison module 907 can compare the shape data to the image data received from the image data store 910,” See at least [0114]; “the shape data comparison module 907 may determine that the last five comparison results output to the shape data adjustment module 908 indicated that the shape data was inconsistent with the robotic data, and output an alert (e.g., indicating that the instrument may be damaged, stuck, or otherwise malfunctioning).” See at least [0120])
Regarding Claim 12,
Graetzel teaches
A method, comprising: (“The systems and methods disclosed herein are directed to surgical robotics, and more particularly to navigation of a medical instrument within a tubular network of a patient's body.” See at least [0002])
receiving, by one or more processors coupled with memory, (“The functions described herein may be stored as one or more instructions on a processor-readable or computer-readable medium. The term “computer-readable medium” refers to any available medium that can be accessed by a computer or processor.” See at least [0149]; “A non-transitory computer readable storage medium having stored thereon instructions that, when executed, cause a processor of a device to at least:” See at least claim 12)
one or more image frames captured via a camera for a medical session with a robotic medical system; (“accessing image data captured by an imaging device located proximal to a tip of the instrument,” See at least [0010]; “The endoscope 118 is a tubular and flexible surgical instrument that is inserted into the anatomy of a patient to capture images of the anatomy (e.g., body tissue). In particular, the endoscope 118 includes one or more imaging devices (e.g., cameras or other types of optical sensors) that capture the images.” See at least [0040]; “Image data may include one or more image frames captured by the imaging device at the instrument tip, as well as information such as frame rates or timestamps.” See at least [0085])
determining, by the one or more processors, based at least in part on the one or more image frames, a visual geometry of an instrument configured to perform a procedure via the robotic medical system during at least a portion of the medical session; (“the shape data comparison module 907 may determine, based on the image data received from the image data store 910, an expected orientation of the instrument (e.g., at or near the distal end of the instrument).” See at least [0115]; “fluoroscopy (X-ray) images can be analyzed by a computer vision algorithm to extract the silhouette of the instrument” See at least [0118])
determining, by the one or more processors, based at least in part on data received from a sensor of a motor of the robotic medical system, a sensed geometry of the instrument; (“FIG. 4D, the system may determine, based on the robotic data, one or more conditions that the endoscope 118 is expected to satisfy (e.g., the curvature value at a given point along the endoscope 118 should be within a predetermined range of values, or should be within a range of values determined based on the pull force on the pull wires and/or the distances that the pull wires have been actuated) … as shown in FIG. 4D, the system may determine, based on the robotic data (e.g., pull force and distances), the robotic-data-based shape prediction 473 exhibiting the predicted curvature 477 at a given point.” See at least [0069]; See at least [0087]; Also see at least figs. 3A and 3B; Examiner Interpretation: At least the sensor that detects pull force on the wires is the sensor of the motor.)
and providing, by the one or more processors, based at least in part on a comparison of the visual geometry with the sensed geometry, a notification of a state of the instrument during the medical session. (“The shape data comparison module 907 may then determine whether the shape data is inconsistent with the expected orientation of the instrument (e.g., the image data indicates that the tip of the instrument is pointing in a direction parallel to the anatomical lumen, but the shape data indicates that the tip of the instrument is pointing at an inner wall of the anatomical lumen).” See at least [0115]; “the shape data comparison module 907 may then determine whether the shape data is inconsistent with the extracted silhouette of the instrument.” See at least [0118]; “the shape data comparison module 907 determines that a mismatch between the shape data and the robotic data has been detected for over a threshold amount of time, and outputs an alert indicating that the instrument may be damaged.” See at least [0120])
Regarding Claim 19,
Graetzel teaches
One or more storage media storing instructions thereon, that, when executed by one or more processors, cause the one or more processors to: (“The functions described herein may be stored as one or more instructions on a processor-readable or computer-readable medium. The term “computer-readable medium” refers to any available medium that can be accessed by a computer or processor.” See at least [0149]; “A non-transitory computer readable storage medium having stored thereon instructions that, when executed, cause a processor of a device to at least:” See at least claim 12)
receive one or more image frames captured via a camera for a manufacturing session for an instrument; (“accessing image data captured by an imaging device located proximal to a tip of the instrument,” See at least [0010]; “The endoscope 118 is a tubular and flexible surgical instrument that is inserted into the anatomy of a patient to capture images of the anatomy (e.g., body tissue). In particular, the endoscope 118 includes one or more imaging devices (e.g., cameras or other types of optical sensors) that capture the images.” See at least [0040]; “Image data may include one or more image frames captured by the imaging device at the instrument tip, as well as information such as frame rates or timestamps.” See at least [0085])
determine, based at least in part on the one or more image frames, a visual geometry of the instrument manufactured to perform a medical procedure via a robotic medical system; (“the shape data comparison module 907 may determine, based on the image data received from the image data store 910, an expected orientation of the instrument (e.g., at or near the distal end of the instrument).” See at least [0115]; “fluoroscopy (X-ray) images can be analyzed by a computer vision algorithm to extract the silhouette of the instrument” See at least [0118])
determine, based at least in part on data received from a sensor of a motor, a sensed geometry of the instrument; (“FIG. 4D, the system may determine, based on the robotic data, one or more conditions that the endoscope 118 is expected to satisfy (e.g., the curvature value at a given point along the endoscope 118 should be within a predetermined range of values, or should be within a range of values determined based on the pull force on the pull wires and/or the distances that the pull wires have been actuated) … as shown in FIG. 4D, the system may determine, based on the robotic data (e.g., pull force and distances), the robotic-data-based shape prediction 473 exhibiting the predicted curvature 477 at a given point.” See at least [0069]; See at least [0087]; Also see at least figs. 3A and 3B; Examiner Interpretation: At least the sensor that detects pull force on the wires is the sensor of the motor.)
and provide, based at least in part on a comparison of the visual geometry with the sensed geometry, a notification of a state of the instrument. (“The shape data comparison module 907 may then determine whether the shape data is inconsistent with the expected orientation of the instrument (e.g., the image data indicates that the tip of the instrument is pointing in a direction parallel to the anatomical lumen, but the shape data indicates that the tip of the instrument is pointing at an inner wall of the anatomical lumen).” See at least [0115]; “the shape data comparison module 907 may then determine whether the shape data is inconsistent with the extracted silhouette of the instrument.” See at least [0118]; “the shape data comparison module 907 determines that a mismatch between the shape data and the robotic data has been detected for over a threshold amount of time, and outputs an alert indicating that the instrument may be damaged.” See at least [0120])
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 factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 3 and 14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Graetzel (US 20200046434 A1) in view of Diolaiti (US 20200182743 A1).
Regarding Claim 3,
Graetzel further teaches
compare the visual geometry with the sensed geometry to determine the state of the instrument (“The shape data comparison module 907 may then determine whether the shape data is inconsistent with the expected orientation of the instrument (e.g., the image data indicates that the tip of the instrument is pointing in a direction parallel to the anatomical lumen, but the shape data indicates that the tip of the instrument is pointing at an inner wall of the anatomical lumen).” See at least [0115]; “the shape data comparison module 907 may then determine whether the shape data is inconsistent with the extracted silhouette of the instrument.” See at least [0118])
Graetzel does not explicitly teach, but Diolaiti teaches
wherein the one or more processors are further configured to: receive an indication that the instrument is installed on an arm of the robotic medical system; and (“the techniques discussed below can help verify correct installation of an end effector or a component thereof, such as before the end effector enters the manipulation site or before certain operations with the end effector is allowed (e.g. operations involving high forces or motions near range of motion limits); and, when an anomaly or an indication of an improperly installed, or incorrectly installed, end effector is determined, an inspection and remedy can be completed before the end effector is allowed to enter the manipulation site or perform particular operations.” See at least [0059])
Though Diolait does not specifically teach the geometry comparison, it teaches ensuring that the end effector/instrument is properly installed before allowing operations of the end effector. In combination with Graetzel, the geometry comparison as taught by Graetzel would occur after and therefore in response to the verification of the correct installation of the end effector.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Diolaiti with a reasonable expectation of success to ensure the end effector is first properly installed to improve safety and efficiency because “an improperly installed, or incorrectly installed, tool can raise the potential for incorrect manipulation, damage to an object within the manipulation site, or can delay or impede procedures.” (See at least [0002])
Regarding Claim 14,
Graetzel further teaches
comparing, by the one or more processors, the visual geometry with the sensed geometry to determine the state of the instrument (“The shape data comparison module 907 may then determine whether the shape data is inconsistent with the expected orientation of the instrument (e.g., the image data indicates that the tip of the instrument is pointing in a direction parallel to the anatomical lumen, but the shape data indicates that the tip of the instrument is pointing at an inner wall of the anatomical lumen).” See at least [0115]; “the shape data comparison module 907 may then determine whether the shape data is inconsistent with the extracted silhouette of the instrument.” See at least [0118])
Graetzel does not explicitly teach, but Diolaiti teaches
comprising: receiving, by the one or more processors, an indication that the instrument is installed on an arm of the robotic medical system; and (“the techniques discussed below can help verify correct installation of an end effector or a component thereof, such as before the end effector enters the manipulation site or before certain operations with the end effector is allowed (e.g. operations involving high forces or motions near range of motion limits); and, when an anomaly or an indication of an improperly installed, or incorrectly installed, end effector is determined, an inspection and remedy can be completed before the end effector is allowed to enter the manipulation site or perform particular operations.” See at least [0059])
Though Diolait does not specifically teach the geometry comparison, it teaches ensuring that the end effector/instrument is properly installed before allowing operations of the end effector. In combination with Graetzel, the geometry comparison as taught by Graetzel would occur after and therefore in response to the verification of the correct installation of the end effector.
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Diolaiti with a reasonable expectation of success to ensure the end effector is first properly installed to improve safety and efficiency because “an improperly installed, or incorrectly installed, tool can raise the potential for incorrect manipulation, damage to an object within the manipulation site, or can delay or impede procedures.” (See at least [0002])
Claim(s) 5, 7, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Graetzel (US 20200046434 A1) in view of Masaki (US 20210369355 A1).
Regarding Claim 5,
Graetzel further teaches
wherein the one or more processors are further configured to: determine a position or orientation (“an imaging device provided at the tip of the endoscope 118 to record images of that space, which can then be transmitted to a computer system such as command console 200 for processing as described herein.” See at least [0057]; “based on the image data received from the image data store 910, an expected orientation of the instrument (e.g., at or near the distal end of the instrument).” See at least [0115])
Graetzel does not explicitly teach, but Masaki teaches
determine a position or orientation of the camera of an endoscope of the robotic medical system; (“the CPU 410 (a processor) of the computer system 400 is programmed to generate a graphical representation of the one or more reference markers in relation to the FOV image acquired by the camera 180 (imaging device). The CPU 410 calculates the change in the orientation of the steerable sheath with respect to the orientation of the imaging device or a change in the orientation of the imaging device with respect to the orientation of the steerable sheath based on the position of a graphical representation (image) of the one or more reference markers in relation to the FOV image.” See at least [0076])
determine the visual geometry of the instrument relative to the position or the orientation of the endoscope; and determine the sensed geometry of the instrument relative to the position or the orientation of the camera on the endoscope. (“The process of FIG. 10 includes namely the steps of: (a) mapping an orientation of the steerable sheath with respect to an orientation of the imaging device based on one or more reference markers or sensor arranged at the distal end of the steerable sheath and/or near the camera (b) determining when the catheter is bent, twist or rotated within the patient's anatomy while acquiring images of the camera field of view (FOV image); (c) reading a signal from the reference marker or sensor; (c2: optionally) reading the Tension/Compression force which is sensed by a strain or displacement sensor 304 located at the handle 200 or control system 300; (d) executing a software algorithm to calculate a change in the orientation of the steerable sheath with respect to the orientation of the imaging device or vice versa based on a signal (e.g. a graphical representation) of the one or more reference markers or sensors in relation to the FOV image; and (e) re-mapping the orientation of the steerable sheath with respect to the orientation of the imaging device by driving control wires 110 in the desired direction to negate the mis-mapping or twist of steerable instrument.” See at least [0097])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Masaki with a reasonable expectation of success “for an improved endoscope system which can prevent negative effects on the user and/or the patient due to mis-mapping between orientation of the camera view, the orientation of the gamepad controller, and the orientation of the catheter tip.” (See at least [0009])
Regarding Claim 7,
Graetzel does not explicitly teach, but Masaki teaches
wherein the one or more processors are further configured to: detect, based at least in part on the one or more image frames, a pattern of a sleeve covering at least a portion of an arm of the robotic medical system comprising the camera; and generate the notification of the state of the instrument based on the pattern of the sleeve. (“The catheter 100 is a catheter sheath which includes one or more reference markers 190 arranged at the distal end (distal tip) of the tool channel 105. In this embodiment, two reference markers including a first reference marker 191 and a second reference marker 192 each having different indicator properties (e.g., red and black colors respectively) are attached at the distal tip of the catheter sheath.” See at least [0068]; “the sensors and/or markers can be arranged in the sheath of the steerable catheter 100, in the frame of the camera, at the distal end of the tool channel 105 and/or along a wire conduit 104.” See at least [0087]; “The camera 180 can image the reference marks in every frame, and the processor is programed to detect the catheter rotation against the camera by analyzing two or more frames (images).” See at least [0070]; “To correct for the mis-mapping of orientation, the CPU 410 (a processor) of the computer system 400 is programmed to generate a graphical representation of the one or more reference markers in relation to the FOV image acquired by the camera 180 (imaging device). The CPU 410 calculates the change in the orientation of the steerable sheath with respect to the orientation of the imaging device or a change in the orientation of the imaging device with respect to the orientation of the steerable sheath based on the position of a graphical representation (image) of the one or more reference markers in relation to the FOV image. The CPU 410 can output an indication for remapping the orientation of the steerable sheath with respect to the orientation of the imaging device.” See at least [0076])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Masaki with a reasonable expectation of success “for an improved endoscope system which can prevent negative effects on the user and/or the patient due to mis-mapping between orientation of the camera view, the orientation of the gamepad controller, and the orientation of the catheter tip.” (See at least [0009])
Regarding Claim 16,
Graetzel further teaches
comprising: determining, by the one or more processors, a position or orientation (“an imaging device provided at the tip of the endoscope 118 to record images of that space, which can then be transmitted to a computer system such as command console 200 for processing as described herein.” See at least [0057]; “based on the image data received from the image data store 910, an expected orientation of the instrument (e.g., at or near the distal end of the instrument).” See at least [0115])
Graetzel does not explicitly teach, but Masaki teaches
comprising: determining, by the one or more processors, a position or orientation of the camera of an endoscope of the robotic medical system; (“the CPU 410 (a processor) of the computer system 400 is programmed to generate a graphical representation of the one or more reference markers in relation to the FOV image acquired by the camera 180 (imaging device). The CPU 410 calculates the change in the orientation of the steerable sheath with respect to the orientation of the imaging device or a change in the orientation of the imaging device with respect to the orientation of the steerable sheath based on the position of a graphical representation (image) of the one or more reference markers in relation to the FOV image.” See at least [0076])
determining, by the one or more processors, the visual geometry of the instrument relative to the position or the orientation of the endoscope; and determining, by the one or more processors, the sensed geometry of the instrument relative to the position or the orientation of the camera on the endoscope. (“The process of FIG. 10 includes namely the steps of: (a) mapping an orientation of the steerable sheath with respect to an orientation of the imaging device based on one or more reference markers or sensor arranged at the distal end of the steerable sheath and/or near the camera (b) determining when the catheter is bent, twist or rotated within the patient's anatomy while acquiring images of the camera field of view (FOV image); (c) reading a signal from the reference marker or sensor; (c2: optionally) reading the Tension/Compression force which is sensed by a strain or displacement sensor 304 located at the handle 200 or control system 300; (d) executing a software algorithm to calculate a change in the orientation of the steerable sheath with respect to the orientation of the imaging device or vice versa based on a signal (e.g. a graphical representation) of the one or more reference markers or sensors in relation to the FOV image; and (e) re-mapping the orientation of the steerable sheath with respect to the orientation of the imaging device by driving control wires 110 in the desired direction to negate the mis-mapping or twist of steerable instrument.” See at least [0097])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Masaki with a reasonable expectation of success “for an improved endoscope system which can prevent negative effects on the user and/or the patient due to mis-mapping between orientation of the camera view, the orientation of the gamepad controller, and the orientation of the catheter tip.” (See at least [0009])
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Graetzel (US 20200046434 A1) in view of Beger (US 20180055546 A1).
Regarding Claim 8,
Graetzel does not explicitly teach, but Beger teaches
wherein the one or more processors are further configured to: detect, based at least in part on the one or more image frames, a marker of the instrument, the marker applied to the instrument; and track, based on the one or more image frames, the marker to determine the visual geometry of the instrument. (“at least one image of the marking device and the article to be taken by means of the detection unit and for the position and shape of the article to be determined by the data processing unit on the basis of an image.” See at least [0017]; “With use of the marking device, the instrument may, accordingly, be a navigated screwing instrument or a navigated drive-in instrument. By means of the instrumentation, it is possible to detect any deformations of the screwing instrument (for example, an out-of-roundness) or of the drive-in instrument. The shape of the instrument, determined on the basis of the one image, can be compared with a shape of the instrument, read, for example, from a storage unit, and a deformation thereby ascertained.” See at least [0041])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Beger with a reasonable expectation of success to simplify determination of the shape of the medical article (See at least [0008]) and to facilitate compensating for instrument deformations (See at least [0041]).
Claim(s) 10 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Graetzel (US 20200046434 A1) in view of Hunter (US 20240374319 A1) and Babu (US 20240081938 A1).
Regarding Claim 10,
Graetzel does not explicitly teach, but Hunter teaches
wherein the one or more processors are further configured to: execute a model trained on machine learning based on the data from (“a machine learning model trained using training images and endoscopic imager positional information generated using any of the sensor-based endoscopic imager tracking methods described within.” See at least [0049]; “Deflection of the endoscope 102 can be determined by determining that the field of view portion of the endoscopic image is shifted off-center in the endoscopic image. FIG. 11B illustrates an example of an endoscopic image 1150 in which the field of view portion of the endoscopic image 1100 (defined by circular perimeter 1152) is shifted upward, as indicated by the distance 1154 between a center 1156 of the endoscopic image 1150 and a center 1158 of field of view portion of the endoscopic image 1100. The center 1158 of field of view portion of the endoscopic image 1100 can be determined by detecting the circular perimeter 1152 (such as using a suitable machine learning algorithm as discussed above) and determining its center. … a warning may be provided to the user of low accuracy of the tracking the location of interest of anatomy if the amount of shift is too great. … In some variations, deflection of the endoscope 102 is sensed by one or more sensors (e.g., strain gauges) of the endoscope 102. The determined deflection can then be combined with motion of the camera head 108 to determine a motion of the distal end of the endoscope 102.” See at least [0092])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Hunter with a reasonable expectation of success to improve accuracy of the endoscope control. (See at least [0092])
Hunter also does not explicitly teach, but Babu teaches
a model trained on machine learning based on the data from the sensor of the motor … to determine the state of the instrument (“a surgical robotic system is provided for anomaly detection. A surgical tool connects by a first number of cables to a respective number of actuators. The surgical tool connects such that actuation of the actuators moves the surgical tool. First sensors are configured to sense positions of the actuators. A processor is configured to detect the anomaly by application of a machine-learned network. The machine-learned network is configured to receive the positions and output a predicted cable force.” See at least [0007]; “the motor or actuator position and load torque are both sensed over time. The sensing is at the actuator 322, along the cable 405, and/or at other parts of the drive chain 500. For example, an encoder 520 senses the position of the actuator 322, and a load sensor 510 senses the load or torque on the actuator 322 and/or the cable 405. Various inputs may be used, such as position as commanded by the user, load resulting from teleoperation, velocity, or any combination thereof. Data (measurements) from the torque sensor (e.g., load sensor 510) alone may be used to detect an anomaly but may be sensitive to a threshold and result in false positives.” See at least [0089])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel and Hunter to further include the teachings of Babu with a reasonable expectation of success to detect anomalies in surgical instruments because “anomalies may occur, such as due to wear of the surgical instrument or drive train or due to interference. Unexpected forces can arise due to factors such as presence of debris, increase in friction due to cable fraying, unexpected external side loads, etc. Such events can lead to instrument cables snapping or impede tool tip motion and adversely affect the surgeon's capability to perform procedures. Earlier reaction or replacement to avoid problems when using with a patient is desired.” (See at least [0004])
Regarding Claim 17
Graetzel does not explicitly teach, but Hunter teaches
comprising: executing, by the one or more processors, a model trained on machine learning based on the data from (“a machine learning model trained using training images and endoscopic imager positional information generated using any of the sensor-based endoscopic imager tracking methods described within.” See at least [0049]; “Deflection of the endoscope 102 can be determined by determining that the field of view portion of the endoscopic image is shifted off-center in the endoscopic image. FIG. 11B illustrates an example of an endoscopic image 1150 in which the field of view portion of the endoscopic image 1100 (defined by circular perimeter 1152) is shifted upward, as indicated by the distance 1154 between a center 1156 of the endoscopic image 1150 and a center 1158 of field of view portion of the endoscopic image 1100. The center 1158 of field of view portion of the endoscopic image 1100 can be determined by detecting the circular perimeter 1152 (such as using a suitable machine learning algorithm as discussed above) and determining its center. … a warning may be provided to the user of low accuracy of the tracking the location of interest of anatomy if the amount of shift is too great. … In some variations, deflection of the endoscope 102 is sensed by one or more sensors (e.g., strain gauges) of the endoscope 102. The determined deflection can then be combined with motion of the camera head 108 to determine a motion of the distal end of the endoscope 102.” See at least [0092])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel to further include the teachings of Hunter with a reasonable expectation of success to improve accuracy of the endoscope control. (See at least [0092])
Hunter also does not explicitly teach, but Babu teaches
a model trained on machine learning based on the data from the sensor of the motor … to determine the state of the instrument; (“a surgical robotic system is provided for anomaly detection. A surgical tool connects by a first number of cables to a respective number of actuators. The surgical tool connects such that actuation of the actuators moves the surgical tool. First sensors are configured to sense positions of the actuators. A processor is configured to detect the anomaly by application of a machine-learned network. The machine-learned network is configured to receive the positions and output a predicted cable force.” See at least [0007]; “the motor or actuator position and load torque are both sensed over time. The sensing is at the actuator 322, along the cable 405, and/or at other parts of the drive chain 500. For example, an encoder 520 senses the position of the actuator 322, and a load sensor 510 senses the load or torque on the actuator 322 and/or the cable 405. Various inputs may be used, such as position as commanded by the user, load resulting from teleoperation, velocity, or any combination thereof. Data (measurements) from the torque sensor (e.g., load sensor 510) alone may be used to detect an anomaly but may be sensitive to a threshold and result in false positives.” See at least [0089])
It would have been obvious to a person having ordinary skill in the art before the effective filing date of the invention to modify the teachings of Graetzel and Hunter to further include the teachings of Babu with a reasonable expectation of success to detect anomalies in surgical instruments because “anomalies may occur, such as due to wear of the surgical instrument or drive train or due to interference. Unexpected forces can arise due to factors such as presence of debris, increase in friction due to cable fraying, unexpected external side loads, etc. Such events can lead to instrument cables snapping or impede tool tip motion and adversely affect the surgeon's capability to perform procedures. Earlier reaction or replacement to avoid problems when using with a patient is desired.” (See at least [0004])
Allowable Subject Matter
Claims 2, 4, 6, 11, 13, 15, and 18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The relevant prior art does not disclose the following:
(Claims 2 and 13) Causing the instrument to pass through the cannula responsive to a detection that the camera is moved away from the longitudinal axis of the cannula by an amount as disclosed by the applicant.
(Claims 4 and 15) Determining the geometries and comparing the geometries responsive to the detection of an event of the medical session has occurred as disclosed by the applicant.
(Claim 6) Suppressing the notification of an error state of the instrument responsive to a detection of an object blocking the view of the instrument as disclosed by the applicant.
(Claims 11 and 18) Determining, based on the comparison of the visual geometry with the sensed geometry, that the instrument decoupled from an arm of the robotic medical system and determining a time at which the instrument decoupled from the arm of the robotic medical system as disclosed by the applicant.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Flynn (US 20240347185 A1) is pertinent because it discusses computer vision analysis to match instrument shape against reference data to confirm the identity of the instrument and generate an alert if the instrument doesn’t pass a test criteria.
Ueda (US 20200015928 A1) is pertinent because it discusses a medical observation apparatus which extracts instrument feature data from a captured image for medical use and compares the extracted features with a shape indicated by the instrument feature data to detect a area including the features indicated by the instrument feature data from the captured image for medical use.
Joshi (US 20230368418 A1) is pertinent because it discusses determining information about a shape of a tracked instrument relative to a reference element coupled to the tracked instrument.
The above mentioned art, evaluated separately and in combination, does not disclose the entirety of limitations of the dependent claims 2, 4, 6, 11, 13, 15, 18, and 20. No prior art has been found at the time of writing this office action to reject the pending claims 2, 4, 6, 11, 13, 15, 18, and 20 under 35 U.S.C. 102 or 103.
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/KARSTON G. EVANS/Examiner, Art Unit 3657
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