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 .
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1 & 18 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The following limitation “using at least one sensor to capture depth data of the surgical site, including from at least one of the reflective markers, to create a depth map of the surgical site” is not described in the specification in such a way as to reasonably convey to one skilled in the relevant art. At no point in the detailed description is it described that that depth data is captured from the reflective markers; however, it is noted that the depth map is “localized relative” to the markers [0173, 0175].
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 & 18 recite the following limitation “using at least one sensor to capture depth data of the surgical site, including from at least one of the reflective markers, to create a depth map of the surgical site” which renders the claim unclear. It is unclear whether the depth data is acquired from the reflective marker or that reflective markers are simply captured in the field of view. For the purposes of this examination the limitation is interpreted as the reflective markers are captured within the field of view.
Claim Rejections - 35 USC § 103
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) 1-4, 6, 9, & 13-19 are rejected under 35 U.S.C. 103 as being unpatentable over Casas (US20210289188A1) in view of Bonny et al (US20210038315A1; hereinafter referred to as Bonny).
Regarding Claim 1, Casas discloses a method for registering a surgical site containing an implant (“ a real-time surgery method and apparatus for displaying a stereoscopic augmented view of a patient from a static or dynamic viewpoint of the surgeon, which employs real-time three-dimensional surface reconstruction for preoperative and intraoperative image registration.” [Abstract], “The preoperative image may be presented, recorded, or registered (referred to hereinafter collectively and individually as “registered”) over the patient, in real time. Thus, the internal anatomical structures of the patient may be blended with the media recorded by the mounted cameras… tracking may be configured to be added to instruments or implants within the preoperative image” [0013-0014]) comprising:
positioning arrays of reflective markers on the patient (“In embodiments, registration is done with the help of optical markers, e.g. color or reflective markers in certain predefined anatomical landmarks of the patient 118 for the 3D scanner system 110, corresponding to markers of the same size and shape placed on the same predefined anatomical landmarks of the patient 118 during the preoperative 102 or intraoperative imaging 106 (e.g. radiopaque markers for CT or x-ray imaging), or virtual markers placed on the predefined anatomical parts in the graphical representation of the images obtained, in the preoperative or intraoperative setting, through the available user interface means 130, 132. In other embodiments, a combination of rigid and nonrigid registration methods are used.” [0085];
using at least one sensor to capture depth data of the surgical site, including from at least one of the reflective markers (“For example, a 3D scanner system 110 may include a laser scanner, a time-of-flight 3D laser scanner, a structured-light 3D scanner, hand-held laser scanner, a time-of-flight camera, a depth camera, or a combination of these or other devices.” [0076], la“In embodiments, registration is done with the help of optical markers, e.g. color or reflective markers in certain predefined anatomical landmarks of the patient 118 for the 3D scanner system 110, corresponding to markers of the same size and shape placed on the same predefined anatomical landmarks of the patient 118 during the preoperative 102 or intraoperative imaging 106 “ [0085], “tracking means 136 may include a tracking camera that works in conjunction with active or passive optical markers that are placed in the scene. In embodiments, the tracking camera may be part of the 3D scanner system 110.” [0107]),
to create a depth map of the surgical site (“More specifically, an output of the surface reconstruction 112 is stored in point sets or depth maps.“ [0086], “in an embodiment using a time-of-flight camera as 3D scanner system 110, multiple real-time images with color and depth information are obtained, and an algorithm (e.g. random forests) is applied to the pixels.” [0128], 3D scanner system comprises multiple tracking means which include a tracking of reflective markers as well as depth sensors to measure depth data);
localizing the surface; calculating an error between the depth map and the surface; and iteratively reorienting the surface with respect to the depth map to minimize the error (“an output of the surface reconstruction 112 is stored in point sets or depth maps. The markerless registration may be completed by applying known methods (e.g. the iterative closest point algorithm, the Curie point depth algorithm, or the scale invariant feature transform algorithm) to the output of volume rendering 104 (e.g. 3D volume image). This markerless registration may be completed by 2D or stereoscopic digital images 108 from previous imaging studies 102 or intraoperative images 106 (e.g. CT scans or MR scans).” [0086], iterative closest point algorithm inherently corrects for error in surface matching).
Casas does not specifically disclose providing a proposed identification of the implant; and reorienting the proposed identification of the implant, wherein the implant is configured to be used in a joint replacement surgery.
However, in a similar field of endeavor, Bonny discloses a method for registering a surgical site containing an implant (“A method for removing an implant attached to a bone during revision joint replacement surgery includes a library of implant models. A series of surface points are collected on the implant with a digitizer. A best match is computed between the collected surface points and an implant model in the library of implant models to register the position of the implant model to the implant” [Abstract])
Bonny also teaches providing a proposed identification of the implant (“determining the implant make/model/size, and registering the manufacturer's 3D model to the segmented implant in the patient, thus providing a transformation matrix between manufacturer's 3D model and the patient's DICOM data. “ [0033]);
And reorienting the proposed identification of the implant (“As used herein, the term “digitizer” refers to a device capable of measuring or designating the location of physical points in three-dimensional space… a non-mechanically tracked digitizer probe (e.g., optically tracked, electromagnetically tracked, acoustically tracked, and equivalents thereof)… the term “digitizing” refers to the collecting, measuring, and/or recording of physical points in space using a digitizer” [0014-0015], “registration of the inventive embodiment for the TKA restoration includes the steps of: digitizing the patient's implant which is rigidly fixed to the patient's operative bone; registering the digitized implant to the nominal 3D model, thus providing the transformation matrix between the digitized implant and the manufacturer's 3D model; and computing the transformation matrix between the digitized implant and the patient's DICOM data, thereby registering the entire patient's operative bone to the set of anatomic landmarks.” [0038]).
wherein the implant is configured to be used in a joint replacement surgery (“The present invention relates generally to the field of computer-aided surgical systems, and more specifically to a new and useful method for performing computer-aided total joint arthroplasty. Total joint replacement (TJR) (also called primary total joint arthroplasty) is a surgical procedure in which the articulating surfaces of a joint are replaced with prosthetic components, or implants.” [0002-0003])
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with providing a proposed identification of the implant; and reorienting the identification of the implant wherein the implant is configured to be used in a joint replacement surgery as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 2, Casas discloses that creating the depth map of the surgical site comprises: imaging the surgical suite using a camera in a structured light modality, wherein the camera includes the at least one sensor (“For example, a 3D scanner system 110 may include a laser scanner, a time-of-flight 3D laser scanner, a structured-light 3D scanner, hand-held laser scanner, a time-of-flight camera, a depth camera, or a combination of these or other devices.” [0076]).
Regarding Claim 3, Casas discloses that creating the depth map of the surgical site comprises: using a depth sensor selected from a group comprising a time of flight sensors, a LIDAR, a laser scanner and an epipolar scanner wherein the at least one sensor includes the depth sensor (“For example, a 3D scanner system 110 may include a laser scanner, a time-of-flight 3D laser scanner, a structured-light 3D scanner, hand-held laser scanner, a time-of-flight camera, a depth camera, or a combination of these or other devices.” [0076]).
Regarding Claim 4, Casas discloses all limitations noted above except that the identification of the implant is an implant model selected from a library of implant models using a surface matching technique.
However, in a similar field of endeavor, Bonny teaches that the identification of the implant is an implant model selected from a library of implant models using a surface matching technique (“A method for removing an implant attached to a bone during revision joint replacement surgery includes a library of implant models. A series of surface points are collected on the implant with a digitizer. A best match is computed between the collected surface points and an implant model in the library of implant models to register the position of the implant model to the implant.” [0007]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with the identification of the implant is an implant model selected from a library of implant models using a surface matching technique as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 6, Casas discloses further comprising: orienting the surface relative to the depth map using an iterative-closest-point (JCP) algorithm (“an output of the surface reconstruction 112 is stored in point sets or depth maps. The markerless registration may be completed by applying known methods (e.g. the iterative closest point algorithm)” [0086]).
Casas does not specifically disclose orienting the implant.
However, in a similar field of endeavor, Bonny teaches orienting the implant (“A method for removing an implant attached to a bone during revision joint replacement surgery includes a library of implant models. A series of surface points are collected on the implant with a digitizer. A best match is computed between the collected surface points and an implant model in the library of implant models to register the position of the implant model to the implant.” [0007]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with orienting the implant as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 9, Casas discloses calculating the error between the depth map and the proposed identification of the implant (“an output of the surface reconstruction 112 is stored in point sets or depth maps. The markerless registration may be completed by applying known methods (e.g. the iterative closest point algorithm)” [0086]).
Casas does not specifically disclose further comprising: identifying critical regions of the implant; wherein the critical regions are given greater weight.
However, in a similar field of endeavor, Bonny teaches further comprising: identifying critical regions of the implant; wherein the critical regions are given greater importance (“A method for removing an implant attached to a bone during revision joint replacement surgery includes a library of implant models. A series of surface points are collected on the implant with a digitizer. A best match is computed between the collected surface points and an implant model in the library of implant models to register the position of the implant model to the implant.” [0007]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with further comprising: identifying critical regions of the implant; wherein the critical regions are given greater weight as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 13, Casas discloses all limitations noted above except that the library contains various models and sizes of implants from various manufacturers.
However, in a similar field of endeavor, Bonny teaches that the library contains various models and sizes of implants from various manufacturers (“A method for removing an implant attached to a bone during revision joint replacement surgery includes a library of implant models. A series of surface points are collected on the implant with a digitizer. A best match is computed between the collected surface points and an implant model in the library of implant models to register the position of the implant model to the implant.” [0007], “determining the implant make/model/size, and registering the manufacturer's 3D model to the segmented implant in the patient” [0037]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with the library contains various models and sizes of implants from various manufacturers as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 14, Casas discloses that the implant is identified using a visual marker disposed on the implant (“The optical markers, alone or in combination with other tracking means, such as inertial measurement units (IMU), may be attached to the 3D scanner system 110, stereoscopic camera system 114, the surgeon 128 (e.g. in the head-mounted stereoscopic display 126), as well as to any instruments and devices 138 (e.g. screws, plates, pins, nails, arthroplasty components, etc., broaches, screwdrivers, motors, etc.) used by the surgeon 128.” [0033]).
Regarding Claim 15, Bonny discloses that the camera is a stereoscopic camera (“the 3D scanner system 110 is composed of a dedicated stereoscopic camera system” [0081]).
Regarding Claim 16, Bonny discloses that the surfaces of the implant are localized using a machine learning model (“computer means 100 may receive a dense 3D point cloud provided by the 3D scanning process, that represents the surface of the target portion of the patient 118 by a point cloud construction algorithm” [0077]).
Regarding Claim 17, Bonny discloses all limitations noted above except that the surfaces of the implant are localized using a navigated probe.
However, in a similar field of endeavor, Bonny teaches that the library contains various models and sizes of implants from various manufacturers (“As used herein, the term “digitizer” refers to a device capable of measuring or designating the location of physical points in three-dimensional space. By way of example but not limitation, the “digitizer” may be: a “mechanical digitizer” having passive links and joints, such as the high-resolution electro-mechanical sensor arm described in U.S. Pat. No. 6,033,415 (which U.S. patent is hereby incorporated herein by reference); a non-mechanically tracked digitizer probe (e.g., optically tracked, electromagnetically tracked, acoustically tracked, and equivalents thereof)” [0014]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with the library contains various models and sizes of implants from various manufacturers as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 18, Casas discloses A system for registering a surgical site containing an implant (“ a real-time surgery method and apparatus for displaying a stereoscopic augmented view of a patient from a static or dynamic viewpoint of the surgeon, which employs real-time three-dimensional surface reconstruction for preoperative and intraoperative image registration.” [Abstract], “The preoperative image may be presented, recorded, or registered (referred to hereinafter collectively and individually as “registered”) over the patient, in real time. Thus, the internal anatomical structures of the patient may be blended with the media recorded by the mounted cameras… tracking may be configured to be added to instruments or implants within the preoperative image” [0013-0014]) comprises:
a surgical computer; and software, executing on the surgical computer and causing the surgical computer to perform the functions of (“the 3D scanner system 110 is composed of time-of-flight cameras and/or other motion tracking devices, which are used for gesture recognition by software means, allowing for interaction of the surgeon 128 or other users with the computer 100 during surgery through the real-time user interface means 132, without touching anything in the operating room. Alternatively or in addition to gesture recognition, voice commands are used to avoid touching the computer 100 or other devices included in this invention and controlled by computer means 100.” [0082]):
registering arrays of reflective markers on the patient (“In embodiments, registration is done with the help of optical markers, e.g. color or reflective markers in certain predefined anatomical landmarks of the patient 118 for the 3D scanner system 110, corresponding to markers of the same size and shape placed on the same predefined anatomical landmarks of the patient 118 during the preoperative 102 or intraoperative imaging 106 (e.g. radiopaque markers for CT or x-ray imaging), or virtual markers placed on the predefined anatomical parts in the graphical representation of the images obtained, in the preoperative or intraoperative setting, through the available user interface means 130, 132. In other embodiments, a combination of rigid and nonrigid registration methods are used.” [0085];
use at least one sensor to capture depth data of the surgical site, including from at least one of the reflective markers (“ In embodiments, registration is done with the help of optical markers, e.g. color or reflective markers in certain predefined anatomical landmarks of the patient 118 for the 3D scanner system 110, corresponding to markers of the same size and shape placed on the same predefined anatomical landmarks of the patient 118 during the preoperative 102 or intraoperative imaging 106 “ [0085], “tracking means 136 may include a tracking camera that works in conjunction with active or passive optical markers that are placed in the scene. In embodiments, the tracking camera may be part of the 3D scanner system 110.” [0107],
to create a depth map of the surgical site (“More specifically, an output of the surface reconstruction 112 is stored in point sets or depth maps.“ [0086], “in an embodiment using a time-of-flight camera as 3D scanner system 110, multiple real-time images with color and depth information are obtained, and an algorithm (e.g. random forests) is applied to the pixels.” [0128], 3D scanner system comprises multiple tracking means which include a tracking of reflective markers as well as depth sensors to measure depth data);
localizing the surface; calculating an error between the depth map and the surface; and iteratively reorienting the surface with respect to the depth map to minimize the error (“an output of the surface reconstruction 112 is stored in point sets or depth maps. The markerless registration may be completed by applying known methods (e.g. the iterative closest point algorithm, the Curie point depth algorithm, or the scale invariant feature transform algorithm) to the output of volume rendering 104 (e.g. 3D volume image). This markerless registration may be completed by 2D or stereoscopic digital images 108 from previous imaging studies 102 or intraoperative images 106 (e.g. CT scans or MR scans).” [0086], iterative closest point algorithm inherently corrects for error in surface matching).
Casas does not specifically disclose providing a proposed identification of the implant; and reorienting the proposed identification of the implant, wherein the implant is configured to be used in a joint replacement surgery.
However, in a similar field of endeavor, Bonny discloses a method for registering a surgical site containing an implant (“A method for removing an implant attached to a bone during revision joint replacement surgery includes a library of implant models. A series of surface points are collected on the implant with a digitizer. A best match is computed between the collected surface points and an implant model in the library of implant models to register the position of the implant model to the implant” [Abstract])
Bonny also teaches providing a proposed identification of the implant (“determining the implant make/model/size, and registering the manufacturer's 3D model to the segmented implant in the patient, thus providing a transformation matrix between manufacturer's 3D model and the patient's DICOM data. “ [0033]);
And reorienting the proposed identification of the implant (“As used herein, the term “digitizer” refers to a device capable of measuring or designating the location of physical points in three-dimensional space… a non-mechanically tracked digitizer probe (e.g., optically tracked, electromagnetically tracked, acoustically tracked, and equivalents thereof)… the term “digitizing” refers to the collecting, measuring, and/or recording of physical points in space using a digitizer” [0014-0015], “registration of the inventive embodiment for the TKA restoration includes the steps of: digitizing the patient's implant which is rigidly fixed to the patient's operative bone; registering the digitized implant to the nominal 3D model, thus providing the transformation matrix between the digitized implant and the manufacturer's 3D model; and computing the transformation matrix between the digitized implant and the patient's DICOM data, thereby registering the entire patient's operative bone to the set of anatomic landmarks.” [0038]).
wherein the implant is configured to be used in a joint replacement surgery (“The present invention relates generally to the field of computer-aided surgical systems, and more specifically to a new and useful method for performing computer-aided total joint arthroplasty. Total joint replacement (TJR) (also called primary total joint arthroplasty) is a surgical procedure in which the articulating surfaces of a joint are replaced with prosthetic components, or implants.” [0002-0003])
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with providing a proposed identification of the implant; and reorienting the identification of the implant wherein the implant is configured to be used in a joint replacement surgery as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Regarding Claim 19, Casas discloses further comprising: a stereoscopic camera in a structured light modality; wherein the surgical computer performs the further function of: imaging the surgical suite using the stereoscopic camera to create the depth map. (“For example, a 3D scanner system 110 may include a laser scanner, a time-of-flight 3D laser scanner, a structured-light 3D scanner, hand-held laser scanner, a time-of-flight camera, a depth camera, or a combination of these or other devices.” [0076], “the 3D scanner system 110 is composed of a dedicated stereoscopic camera system” [0081]).
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Casas in view of Bonny as applied to Claim 1 above, and further in view of Qiu et al (B. Qiu et al., “Automatic segmentation of mandible from conventional methods to deep learning—a review,” Journal of Personalized Medicine, vol. 11, no. 7, p. 629, Jul. 2021; hereinafter referred to as Qiu).
Regarding Claim 7, Casas discloses that the error between the orientation of the surface and the depth map is calculated (“an output of the surface reconstruction 112 is stored in point sets or depth maps. The markerless registration may be completed by applying known methods (e.g. the iterative closest point algorithm, the Curie point depth algorithm, or the scale invariant feature transform algorithm) to the output of volume rendering 104 (e.g. 3D volume image). This markerless registration may be completed by 2D or stereoscopic digital images 108 from previous imaging studies 102 or intraoperative images 106 (e.g. CT scans or MR scans).” [0086], iterative closest point algorithm inherently corrects for error in surface matching).
Casas does not specifically disclose orienting the implant; and calculating the error using a Hausdorff distance.
However, Bonny teaches orienting the implant (“As used herein, the term “digitizer” refers to a device capable of measuring or designating the location of physical points in three-dimensional space… a non-mechanically tracked digitizer probe (e.g., optically tracked, electromagnetically tracked, acoustically tracked, and equivalents thereof)… the term “digitizing” refers to the collecting, measuring, and/or recording of physical points in space using a digitizer” [0014-0015], “registration of the inventive embodiment for the TKA restoration includes the steps of: digitizing the patient's implant which is rigidly fixed to the patient's operative bone; registering the digitized implant to the nominal 3D model, thus providing the transformation matrix between the digitized implant and the manufacturer's 3D model; and computing the transformation matrix between the digitized implant and the patient's DICOM data, thereby registering the entire patient's operative bone to the set of anatomic landmarks.” [0038]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with orienting the implant as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Bonny does not specifically teach calculating the error using a Hausdorff distance
However, in a similar field of endeavor, Qiu teaches segmentation methods for anatomical structures and implants placed on the patient [Abstract]
Qiu also teaches calculating the error using a Hausdorff distance (“In addition to the differences in the used dataset, the results are evaluated and presented in different ways in the reviewed papers. Moreover, there are no standard metrics for the segmentation evaluation, so different evaluation metrics are used to report the segmentation performance. For segmentation, the evaluation metrics are mainly divided into three categories: overlap-based metrics, distance-based metrics, and volume-based metrics… The most commonly used overlap-based metrics include the Dice similarity coefficient (Dice), Sensitivity (Sen), false positive volume fraction (FPVF) [35], false negative volume fraction (FNVF) [35], etc. To measure the contour difference between automatic and manual segmentation, the most commonly used metrics are distance-based metrics. In the context of mandibular segmentation, the following distance-based metrics have been frequently used: average symmetric surface distance (ASD), Hausdorff distance (HD), 95th-percentile Hausdorff distance (95HD), mean square error (MSE) [36], and root mean square error (RMSE) [36].” [3.3. Evaluation Metrics] .
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with calculating the error using a Hausdorff distance as taught by Qiu, because In some medical image segmentation tasks, the volume of the object is also very important for treatment planning, and the metric based on volume is helpful to evaluate the performance of the segmentation method. Volume overlap error and volume error are the common indices to evaluate the results of mandibular segmentation [3.3. Evaluation Metrics].
Regarding Claim 8, Casas discloses that the error between the orientation of the surface and the depth map is calculated (“an output of the surface reconstruction 112 is stored in point sets or depth maps. The markerless registration may be completed by applying known methods (e.g. the iterative closest point algorithm, the Curie point depth algorithm, or the scale invariant feature transform algorithm) to the output of volume rendering 104 (e.g. 3D volume image). This markerless registration may be completed by 2D or stereoscopic digital images 108 from previous imaging studies 102 or intraoperative images 106 (e.g. CT scans or MR scans).” [0086], iterative closest point algorithm inherently corrects for error in surface matching).
Casas does not specifically disclose orienting the implant; and calculating the error using a dice coefficient.
However, Bonny teaches orienting the implant (“As used herein, the term “digitizer” refers to a device capable of measuring or designating the location of physical points in three-dimensional space… a non-mechanically tracked digitizer probe (e.g., optically tracked, electromagnetically tracked, acoustically tracked, and equivalents thereof)… the term “digitizing” refers to the collecting, measuring, and/or recording of physical points in space using a digitizer” [0014-0015], “registration of the inventive embodiment for the TKA restoration includes the steps of: digitizing the patient's implant which is rigidly fixed to the patient's operative bone; registering the digitized implant to the nominal 3D model, thus providing the transformation matrix between the digitized implant and the manufacturer's 3D model; and computing the transformation matrix between the digitized implant and the patient's DICOM data, thereby registering the entire patient's operative bone to the set of anatomic landmarks.” [0038]).
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas as outlined above with orienting the implant as taught by Bonny, because there exists a need for a more effective process to adequately remove the previous implant, any bone cement, and prepare a new cavity for a revision implant without further compromising the structure of the bone [0006].
Bonny does not specifically teach calculating the error using a dice coefficient.
However, in a similar field of endeavor, Qiu teaches calculating the error using a dice coefficient (“In addition to the differences in the used dataset, the results are evaluated and presented in different ways in the reviewed papers. Moreover, there are no standard metrics for the segmentation evaluation, so different evaluation metrics are used to report the segmentation performance. For segmentation, the evaluation metrics are mainly divided into three categories: overlap-based metrics, distance-based metrics, and volume-based metrics… The most commonly used overlap-based metrics include the Dice similarity coefficient (Dice), Sensitivity (Sen), false positive volume fraction (FPVF) [35], false negative volume fraction (FNVF) [35], etc. To measure the contour difference between automatic and manual segmentation, the most commonly used metrics are distance-based metrics. In the context of mandibular segmentation, the following distance-based metrics have been frequently used: average symmetric surface distance (ASD), Hausdorff distance (HD), 95th-percentile Hausdorff distance (95HD), mean square error (MSE) [36], and root mean square error (RMSE) [36].” [3.3. Evaluation Metrics] .
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with calculating the error using a dice coefficient as taught by Qiu, because In some medical image segmentation tasks, the volume of the object is also very important for treatment planning, and the metric based on volume is helpful to evaluate the performance of the segmentation method. Volume overlap error and volume error are the common indices to evaluate the results of mandibular segmentation [3.3. Evaluation Metrics].
Claims 5, 10-12, & 20 are rejected under 35 U.S.C. 103 as being unpatentable over Casas in view of Bonny as applied to Claim 1 & 18 above, and further in view of Modrow et al (US20140005685A1; hereinafter referred to as Modrow)
Regarding Claim 5, Casas in view of Bonny discloses all limitations noted above except that during creation of the depth map, a confidence metric is provided that characterizes a likelihood of a match between the depth map and an implant model in the library.
However, in a similar field of endeavor, Modrow teaches a method for preparing the reconstruction of a damaged bone structure using an implant [Abstract].
Modrow also teaches during creation of the depth map, a confidence metric is provided that characterizes a likelihood of a match between the depth map and an implant model in the library (“The third step of the method involves selecting an implant and providing a shape dataset which represents the shape of the implant, wherein “selecting” means in particular that the computer automatically picks out one of the available implants.” [0009] “In a fourth step, the selected implant is positioned in order to determine an implant position… Automatic implant positioning is in particular a step of virtually positioning the implant and is preferably performed on the structure dataset and the shape dataset by the computer.” [0010], “In a fifth step, a determination is made as to whether or not the selected implant is suitable, and the method returns to the third step if the implant is determined to not be suitable. The determination is preferably made automatically by the computer, for example by comparing the target structure with the positioned shape dataset or a combination of the structure dataset and the positioned shape dataset. The implant is suitable if the shape of the implant matches the shape of the target structure or a part of the target structure to a predetermined level of accuracy.” [0011]
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with during creation of the depth map, a confidence metric is provided that characterizes a likelihood of a match between the depth map and an implant model in the library as taught by Modrow, because of improving and simplifying preparation of the reconstruction, in particular finding a suitable implant for the affected bone structure [0002].
Regarding Claim 10, Casas in view of Bonny discloses all limitations noted above except that the proposed identification of the implant is considered a positive match to the actual implant if the minimized error falls below a predetermined threshold.
However, in a similar field of endeavor, Modrow teaches a method for preparing the reconstruction of a damaged bone structure using an implant [Abstract].
Modrow also teaches that the proposed identification of the implant is considered a positive match to the actual implant if the minimized error falls below a predetermined threshold (“The third step of the method involves selecting an implant and providing a shape dataset which represents the shape of the implant, wherein “selecting” means in particular that the computer automatically picks out one of the available implants.” [0009] “In a fourth step, the selected implant is positioned in order to determine an implant position… Automatic implant positioning is in particular a step of virtually positioning the implant and is preferably performed on the structure dataset and the shape dataset by the computer.” [0010], “In a fifth step, a determination is made as to whether or not the selected implant is suitable, and the method returns to the third step if the implant is determined to not be suitable. The determination is preferably made automatically by the computer, for example by comparing the target structure with the positioned shape dataset or a combination of the structure dataset and the positioned shape dataset. The implant is suitable if the shape of the implant matches the shape of the target structure or a part of the target structure to a predetermined level of accuracy.” [0011]
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with the proposed identification of the implant is considered a positive match to the actual implant if the minimized error falls below a predetermined threshold as taught by Modrow, because of improving and simplifying preparation of the reconstruction, in particular finding a suitable implant for the affected bone structure [0002].
Regarding Claim 11, Casas in view of Bonny discloses all limitations noted above except that the identification of the implant is considered a negative match to the actual implant if the minimize error is above the predetermined threshold.
However, in a similar field of endeavor, Modrow teaches a method for preparing the reconstruction of a damaged bone structure using an implant [Abstract].
Modrow also teaches that the identification of the implant is considered a negative match to the actual implant if the minimize error is above the predetermined threshold (“The third step of the method involves selecting an implant and providing a shape dataset which represents the shape of the implant, wherein “selecting” means in particular that the computer automatically picks out one of the available implants.” [0009] “In a fourth step, the selected implant is positioned in order to determine an implant position… Automatic implant positioning is in particular a step of virtually positioning the implant and is preferably performed on the structure dataset and the shape dataset by the computer.” [0010], “In a fifth step, a determination is made as to whether or not the selected implant is suitable, and the method returns to the third step if the implant is determined to not be suitable. The determination is preferably made automatically by the computer, for example by comparing the target structure with the positioned shape dataset or a combination of the structure dataset and the positioned shape dataset. The implant is suitable if the shape of the implant matches the shape of the target structure or a part of the target structure to a predetermined level of accuracy.” [0011]
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with the proposed identification of the implant is considered a negative match to the actual implant if the minimize error is above the predetermined threshold as taught by Modrow, because of improving and simplifying preparation of the reconstruction, in particular finding a suitable implant for the affected bone structure [0002].
Regarding Claim 12, Casas in view of Bonny discloses all limitations noted above except further comprising: providing a new identification of the implant if the minimized error falls above the predetermined threshold.
However, in a similar field of endeavor, Modrow teaches a method for preparing the reconstruction of a damaged bone structure using an implant [Abstract].
Modrow also teaches providing a new identification of the implant if the minimized error falls above the predetermined threshold (“The third step of the method involves selecting an implant and providing a shape dataset which represents the shape of the implant, wherein “selecting” means in particular that the computer automatically picks out one of the available implants.” [0009] “In a fourth step, the selected implant is positioned in order to determine an implant position… Automatic implant positioning is in particular a step of virtually positioning the implant and is preferably performed on the structure dataset and the shape dataset by the computer.” [0010], “In a fifth step, a determination is made as to whether or not the selected implant is suitable, and the method returns to the third step if the implant is determined to not be suitable. The determination is preferably made automatically by the computer, for example by comparing the target structure with the positioned shape dataset or a combination of the structure dataset and the positioned shape dataset. The implant is suitable if the shape of the implant matches the shape of the target structure or a part of the target structure to a predetermined level of accuracy.” [0011]
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with providing a new identification of the implant if the minimized error falls above the predetermined threshold as taught by Modrow, because of improving and simplifying preparation of the reconstruction, in particular finding a suitable implant for the affected bone structure [0002].
Regarding Claim 20, Casas in view of Bonny discloses all limitations noted above except the surgical computer performs the further function of: providing a new identification of the implant if the minimized error falls above the predetermined threshold.
However, in a similar field of endeavor, Modrow teaches a method for preparing the reconstruction of a damaged bone structure using an implant [Abstract].
Modrow also teaches providing a new identification of the implant if the minimized error falls above the predetermined threshold (“The third step of the method involves selecting an implant and providing a shape dataset which represents the shape of the implant, wherein “selecting” means in particular that the computer automatically picks out one of the available implants.” [0009] “In a fourth step, the selected implant is positioned in order to determine an implant position… Automatic implant positioning is in particular a step of virtually positioning the implant and is preferably performed on the structure dataset and the shape dataset by the computer.” [0010], “In a fifth step, a determination is made as to whether or not the selected implant is suitable, and the method returns to the third step if the implant is determined to not be suitable. The determination is preferably made automatically by the computer, for example by comparing the target structure with the positioned shape dataset or a combination of the structure dataset and the positioned shape dataset. The implant is suitable if the shape of the implant matches the shape of the target structure or a part of the target structure to a predetermined level of accuracy.” [0011]
It would have been obvious to an ordinary skilled person in the art before the effective filing
date of the claimed invention to modify the system of Casas in view of Bonny as outlined above with providing a new identification of the implant if the minimized error falls above the predetermined threshold as taught by Modrow, because of improving and simplifying preparation of the reconstruction, in particular finding a suitable implant for the affected bone structure [0002].
Response to Arguments
Applicant's arguments filed 04/01/2026 have been fully considered but they are not persuasive.
Regarding the U.S.C. 103 rejection of Claims 1-4, 6, 13-19 the applicant argues the following:
Applicant respectfully submits that Casas in view of Bonny fails to disclose at least the features "using at least one sensor to capture depth data of the surgical site, including from at least one of the reflective markers, to create [[ing]] a depth map of the surgical site." In the Office Action, the Examiner argues that Casas discloses most of the features of claim 1, and relies on Bonny for alleviating the deficiencies of Casas. Applicant respectfully disagrees.
However, it is first noted that in view of the 112(a) and 112(b) rejections noted above the limitation in question is both not clearly taught in the specification and indefinite in its current written form. The only mention of the reflective markers with respect to the depth map in the Applicant’s spec can be seen in [0173] & [0175] which are provided below as well as [0164] which expressly teaches that the reflective markers are only used for tracking of bone portions.
[0164] “The arrays of reflective markers serve to localize and track the tibia and the femur with respect to the surgical site during the surgery.”
[0173] “…The depth map is used only to register the position and orientation of the implant relative to the implanted reflective markers in the femur and tibia, and not to identify the implant.”
[0175] “…Once the implant is identified at 508 and oriented at 514, and the minimized error is below the threshold, the stereoscopic camera 115 toggles, at 518, from a structured light or other depth sensing modality to a conventional IR navigation modality. Because the patient was fitted with IR markers at 502, the depth map and the implant model are localized relative to these markers.”
As seen in the 2 examples above the depth map is not created based on depth data gathered from the reflective markers instead the already generated depth map is localized relative to the reflective markers. The spec does clarify that the creation of the depth is done by using a multitude of differing sensors that collect depth information [0165-0167] similar to Casas paragraphs [0076], [0128], & [0139].
In view of the Applicant’s spec the limitations now raises indefiniteness questions, as postured in the amendment and applicant argument it is being presented that the creation of the depth map is dependent on the reflective markers; however, as mentioned above the creation of the depth map has no relation to the reflective markers.
Under broadest reasonable interpretation of the limitation in question, it is now being interpreted as the depth sensor merely having reflective markers within its field of view and the depth map being created through a separate process of the reflective markers.
Casas teaches a system which has reflective markers placed on a surgical site being tracked by a 3D scanner device 110 (“tracking means 136 may include a tracking camera that works in conjunction with active or passive optical markers that are placed in the scene. In embodiments, the tracking camera may be part of the 3D scanner system 110.” [0107])
Casas also teaches that the 3D scanner system also comprises depth sensors measuring depth information of the surgical site which is used to create a depth map (“More specifically, an output of the surface reconstruction 112 is stored in point sets or depth maps.“ [0086], “in an embodiment using a time-of-flight camera as 3D scanner system 110, multiple real-time images with color and depth information are obtained, and an algorithm (e.g. random forests) is applied to the pixels.” [0128], 3D scanner system comprises multiple tracking means which include a tracking of reflective markers as well as depth sensors to measure depth data).
In view of the 112 rejections and broadest reasonable interpretation of the amended claims Casas in view of Bonny does teach “using at least one sensor to capture depth data of the surgical site, including from at least one of the reflective markers, to create [[ing]] a depth map of the surgical site”.
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 STEVEN MALDONADO whose telephone number is 703-756-1421. The examiner can normally be reached 8:00 am-4:00 pm PST M-Th Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at
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/Steven Maldonado/
Patent Examiner, Art Unit 3797
/CHRISTOPHER KOHARSKI/Supervisory Patent Examiner, Art Unit 3797
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