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 .
Response to Arguments
Applicant’s arguments in combination with amendments, see remarks and claims, with respect to the rejection(s) of claim(s) under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of the following as detailed below.
Allowable Subject Matter
Claims 3-4 , 11-12 and 17 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.
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
Claims 1, 5-10, 13-14, 16, 18-19 and 33 is/are rejected under 35 U.S.C. 103 as being unpatentable over us 20210393336 to Sganga et al. (hereinafter “Sganga”).
Regarding claim 1. (Currently Amended) Sganga discloses system for estimating and visualizing trajectories of an interventional device guided by a robot and configured for insertion into an anatomical structure of a subject (abstract, para 0006, 0107), the system comprising: at least one processor (para 0007); and a non-transitory memory for storing machine executable instructions that, when executed by the at least one processor, cause the at least one processor to (para 0007): receive image data from a current image of the anatomical structure (para 0008 “medical image”), the current image showing a current position of the interventional device with respect to the anatomical structure (para 0008 “medical image comprises determining the current position and current direction of the distal tip”); receive at least one untriggered control input for controlling the robot to guide future movement of the interventional device from the current position (para 0006, “user input selection of a target waypoint relative to the medial image”; 0128 “command or user input”); predict at least one trajectory of the interventional device in the current image fromfrom one waypoint to another waypoint inputted by the user [] utilize one or more machine learning and/or artificial intelligence algorithms to determine a pathway for the tool to advance”), wherein the model is configured to predict trajectories of the interventional device based on a first input of the image data of the interventional device in the anatomical structure and on a second input ofthe later step is considered to be determining whether the predicted trajectory is acceptable or needing further modification), wherein a trigger command is provided when the predicted trajectory is determined to be acceptable (id), and wherein the trigger command is for triggering the at least one untriggered control input to control the robot to guide movement of the interventional device according to the at least one triggered control input (para 0132 “display the action the robot will take and ask for confirmation (i.e., trigger) before executing the action”).
Regarding claim 5. (Previously Presented) Sganga discloses the system of claim 1, wherein the executed instructions further cause the at least one processor to: provide a user interface configured for allowing a user to send said trigger command (para 0132 “the system and/or software operating on the system may display the action the robot will take and may ask for confirmation by the user or set of users before executing the action”).
Regarding claim 6. (Previously Presented) Sganga discloses the system of claim 5, wherein the user interface is further configured to provide to the user information regarding the at least one predicted trajectory (para 0132) to assist the user in deciding whether a predicted trajectory is acceptable, and thereby assisting the user to provide the trigger command (non-functional language, no patentable weight).
Regarding claim 7. (Currently Amended) Sganga discloses the system of claim 1, wherein the executed instructions further cause the at least one processor to:receive at least one new untriggered control input for controlling the robot to alternatively guide the future movement of the interventional device from the current position when the trigger command is not provided (para 0132 “select a new target location”).
Regarding claim 8. (Previously Presented) Sganga discloses the system of claim 1, wherein said model is a trained model configured to predict trajectories of the interventional device based on training data from previous images of the interventional device in the anatomical structure and corresponding control inputs to the robot for guiding movement of the interventional device as shown in the previous images (para 0108, 0136, etc.).
Regarding claim 9. (Previously Presented) Sganga discloses the system of claim 1, wherein the executed instructions further cause the at least one processor to: perform a training of said model with regard to predicting trajectories of the interventional device based on training data from at least one of previous images of the interventional device in the anatomical structure and the received image data and at least one of previous control inputs corresponding to the previous images and the at least one untriggered control input to the robot for guiding movement of the interventional device as shown in the previous images (para 0108, 0136, etc.).
Regarding claim 10. (Previously Presented) Sganga discloses the system of claim 1, wherein said model is a convolutional- long-short term memory (LSTM) neural network model (para 0188, MPEP 2143 (B) Simple substitution of one known element for another to obtain predictable results).
Regarding claim 13. (Previously Presented) Sganga discloses the system of claim 1, wherein the model is further configured to predict trajectories of the interventional device further based on an input of shape data of the interventional device shown in the image data of the first input (para 0066 “process the various images provided to it and determine the location and/or configuration (e.g., pose, shape, and/or orientation) of any instrumentation”)
Regarding claim 14. (Previously Presented) Sganga discloses the system of claim 1, wherein the model is further configured to process temporal sequences of imaging data such that the trajectories are progressively predicted over time, when the interventional device moves (0086, 0140, 0174 “update”).
Regarding claim 16. (Previously Presented) Sganga discloses the system of claim 1, wherein the executed instructions further cause the at least one processor to: display the at least one predicted trajectory of the interventional device overlaid on the current image of the anatomical structure for a user to determine whether the at least one predicted trajectory is acceptable (para 0008, 0132 “the system and/or software operating on the system may display the action the robot will take and may ask for confirmation by the user or set of users before executing the action”).
Regarding claim 18. (Previously Presented) Sganga discloses the system of claim 1, wherein the executed instructions further cause the at least one processor to: receive additional image data from additional images of the anatomical structure after triggering the untriggered input (para 0006, etc. “loop”); and display an actual trajectory of the interventional device overlaid on the current image, along with the predicted trajectory, after triggering the untriggered control inputs (para 0006, 0125, 0137).
Regarding claim 19. (Previously Presented) Sganga discloses the system of claim 1, further comprising: a robot controller configured to enable control of the robot in accordance with the at least one triggered control inputs (para 0119, 0140).
Regarding claim 33. (Previously Presented) Sganga discloses a method of estimating and visualizing trajectories of an interventional device guided by a robot and configured for insertion into an anatomical structure of a subject (abstract, para 0006, 0107), the method comprising: performing training of a neural network model with regard to predicting trajectories of the interventional device based on training data from previous images of the interventional device and corresponding control inputs to the robot for guiding movement of the interventional device as shown in the previous images (para 0108, 0136, etc.); receiving image data from at least one image of the anatomical structure, the at least one image showing a current position of the interventional device with respect to the anatomical structure (para 0008 “medical image comprises determining the current position and current direction of the distal tip”); receiving untriggered control inputs for controlling the robot to guide future movement of the interventional device from the current position (para 0006, “user input selection of a target waypoint relative to the medial image”; 0128 “command or user input”); predicting a trajectory of the interventional device in the at least one image by applying the image data and the untriggered control inputs to the trained neural network model (para 0006, 0007, “generate at least one current trajectory command”, para 0107 “the system can be configured to automatically, dynamically, and/or algorithmically calculate or determine a pathway for the tool to proceed from one waypoint to another waypoint inputted by the user [] utilize one or more machine learning and/or artificial intelligence algorithms to determine a pathway for the tool to advance”); displaying the predicted trajectory of the interventional device overlaid on the at least one image of the anatomical structure (para 0008, 0132 “the system and/or software operating on the system may display the action the robot will take and may ask for confirmation by the user or set of users before executing the action”); triggering the untriggered control inputs to control the robot to guide movement of the interventional device according to the triggered control inputs when the predicted trajectory is determined to be acceptable (para 0108 “the system can be configured to use one or more machine learning and/or artificial intelligence algorithms to determine initially a suggested pathway or trajectory between two waypoints, and the system can further be configured to use one or more machine learning and/or artificial intelligence algorithms to improve such pathways or trajectories that it suggests”, the later step is considered to be determining whether the predicted trajectory is acceptable or needing further modification); and receiving new untriggered control inputs for controlling the robot to alternatively guide the future movement of the interventional device from the current position when the predicted trajectory is determined to be not acceptable para 0132 “display the action the robot will take and ask for confirmation (i.e., trigger) before executing the action”, para 0132 “select a new target location”).
Claims 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over us 20210393336 to Sganga in view of WO2020173814A1 to Toporek et al. (hereinafter “Toporek” – 2020/09/03)
Regarding claim 15. (Previously Presented) Sganga discloses the system of claim 1, wherein the executed instructions further cause the at least one processor to estimate an uncertainty of the at least one predicted trajectory using the model (para 0073), but fails to disclose to display the estimated uncertainty with the at least one predicted trajectory overlaid on the current image of the anatomical structure.
Toporek, from a similar field of endeavor teaches showing confidence ratio of the prediction to the user. (“forward predictive model 60b, fig. 6D, see p. 22, l 30-p 25, l 26). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the disclosure of Bono with the teachings of Toporek, to use a machine learning model, to provide the predictable result of improving accuracy, speed and providing confidence ratio to the user.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 SANA SAHAND whose telephone number is (571)272-6842. The examiner can normally be reached M-Th 8:30 am -5:30 pm; F 9 am-3 pm.
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/SANA SAHAND/Examiner, Art Unit 3796
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