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 .
Notice to Applicant
Claims 1-20 are pending.
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.
1. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-20 are directed to managing the performance of a medical procedure, which is considered managing personal behavior. Managing personal behaviors fall within a subject matter grouping of abstract ideas which the Courts have considered ineligible (Certain methods of organizing human activity). The claims do not integrate the abstract idea into a practical application, and do not include additional elements that provide an inventive concept (are sufficient to amount to significantly more than the abstract idea).
Under step 1 of the Alice/Mayo framework, it must be considered whether the claims are directed to one of the four statutory classes of invention. In the instant case, claims 1-12 recite a system comprising a processor and a memory. Claims 13-18 recite a method and at least one step. Claims 19-20 recite a non-transitory computer-readable medium. Therefore, the claims are each directed to one of the four statutory categories of invention (manufacture, process, apparatus).
Under step 2A of the Alice/Mayo framework, it must be considered whether the claims are “directed to” an abstract idea. That is, whether the claims recite an abstract idea and fail to integrate the abstract idea into a practical application.
Regarding independent claim 1, the claim sets forth a system for managing the performance of a medical procedure, in the following limitations:
receive a plurality of image frames related to a medical procedure;
transform the plurality of image frames to a plurality of feature vectors;
cluster the plurality of feature vectors into a plurality of clusters;
generate a run-length encoded data stream based at least in part on the plurality of clusters; and
transmit the run-length encoded data stream to manage performance of the medical procedure.
The above-recited limitations collect, transform and transmit medical data/video to a server with the purpose or managing the performance of a medical procedure. This arrangement amounts to managing personal behavior or interactions between people. Such concepts have been considered ineligible certain methods of organizing human activity by the Courts (See MPEP 2106.04(a)).
Claim 1 does recite additional elements:
via a robotic medical system
performed by the robotic medical system
via one or more models trained with machine learning on historical images of medical procedures
via the one or more models
via a network
to one or more servers remote from the one or more processors
These additional elements merely amount to the general application of the abstract idea to a technological environment (“via a robotic medical system”, ”performed by the robotic medical system”, “via one or more models trained with machine learning on historical images of medical procedures”, “via the one or more models”, “via a network”, “to one or more servers remote from the one or more processors”) and insignificant pre-and-post solution activity (receive, transform, cluster, generate, and transmit). The specification makes clear the general-purpose nature of the technological environment. Paragraphs 38, 41, 45-46, 51, and 118-121 indicate that while exemplary general purpose systems may be specific for descriptive purposes, any elements or combinations of elements capable of implementing the claimed invention are acceptable. That is, the technology used to implement the invention is not specific or integral to the claim.
Therefore, considered both individually and as an ordered combination, the additional elements do no more than generally link the use of the abstract idea to a particular technological environment or field of use. That is, given the generality with which the additional limitations are recited, the limitations do not implement the abstract idea with, or use the abstract idea in conjunction with, a particular machine or manufacture that is integral to the claim. Additionally, the claims do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, do not effect a transformation or reduction of a particular article to a different state or thing; and do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea. Accordingly, the Examiner concludes that the claim fails to integrate the abstract idea into a practical application, and is therefore “directed to” the abstract idea.
Under step 2B of the Alice/Mayo framework, it must finally be considered whether the claim includes any additional element or combination of elements that provide an inventive concept (i.e., whether the additional element or elements are sufficient to amount to significantly more than the abstract idea). As indicated above, considered both individually and as an ordered combination, the additional elements do not implement the abstract idea with, or use the abstract idea in conjunction with, a particular machine or manufacture that is integral to the claim, do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition, do not effect a transformation or reduction of a particular article to a different state or thing, and do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the abstract idea
Further, the additional elements (recited above) simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. Communicating information (i.e., receiving or transmitting data over a network) has been repeatedly considered well-understood, routine, and conventional activity by the Courts (See MPEP 2106.05(d)). Accordingly, the Examiner asserts that the additional elements, considered both individually, and as an ordered combination, do not provide an inventive concept, and the claim is ineligible for patent.
Independent Claims 13 and 19 are parallel in scope to claim 1 and ineligible for similar reasons.
Dependent claims
Each of these steps of the dependent claims 2-12, 14-18, and 20 only serve to further limit or specify the features of independent claims 1, 13, and 19 accordingly, and hence are nonetheless directed towards fundamentally the same abstract idea as the independent claim and utilize the additional elements already analyzed in the expected manner.
Regarding Claim 2
Claim 2 sets forth:
reduce image loss between the plurality of image frames and the plurality of feature vectors.
Such a recitation merely embellishes the abstract idea of managing the performance of a medical procedure, including managing personal behavior. While the claim does set forth the additional limitation of “train, using machine learning, the one or more models”, this recitation is similar to the additional limitations in claim 1, as it does no more than generally link the use of the abstract idea to a particular technological environment. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Additionally, the following dependent claims set forth additional limitations: Claims 3, 4, 5, and 20 recite train, using machine learning, the one or more models; claim 7 recites train, using machine learning, an encoder and one or more servers; claims 9-11 recite using one or more second models; claims 14 and 16 recite training, by the one or more processors, using machine learning, the one or more models; claim 15 recites executing, by the one or more processors, a function to train the one or more models; claim 17 recites training, by the one or more processors, using machine learning, an encoder and one or more servers; and claim 18 recites by the one or more processors. These recitations are similar to the additional limitations in claim 1, as it does no more than generally link the use of the abstract idea to a particular technological environment. As such, it does not integrate the abstract idea into a practical application, and does not provide an inventive concept. Accordingly, the claim does not confer eligibility on the claimed invention and is ineligible for similar reasons to claim 1.
Allowable Subject Matter
The following is a statement of reasons for the indication of allowable subject matter:
The would be allowable if rewritten to overcome the current 35 U.S.C. 101 rejections of claims 1-20.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure fails to teach or disclose the following limitations:
receive, via a robotic medical system, a plurality of image frames related to a medical procedure performed by the robotic medical system;
transform, via one or more models trained with machine learning on historical images of medical procedures, the plurality of image frames to a plurality of feature vectors;
cluster, via the one or more models, the plurality of feature vectors into a plurality of clusters;
generate a run-length encoded data stream based at least in part on the plurality of clusters; and
transmit, via a network, the run-length encoded data stream to one or more servers remote from the one or more processors to manage performance of the medical procedure.
TOOL TRACKING SYSTEMS AND METHODS FOR IMAGE GUIDED SURGERY (US 20090088634 A1), Zhao, et al. teaches a tool tracking system is disclosed including a computer usable medium having computer readable program code to receive images of video frames from at least one camera and to perform image matching of a robotic instrument to determine video pose information of the robotic instrument within the images. The tool tracking system further includes computer readable program code to provide a state-space model of a sequence of states of corrected kinematics information for accurate pose information of the robotic instrument. The state-space model receives raw kinematics information of mechanical pose information and adaptively fuses the mechanical pose information and the video pose information together to generate the sequence of states of the corrected kinematics information for the robotic instrument. Additionally disclosed are methods for image guided surgery.
Robotic surgical systems with multi-modality imaging for performing surgical steps (US 11672614 B1), Roh, et al. teaches automated and robotic surgical procedures and specifically to apparatuses for performing robotic surgical procedures using automated disease detection by multiple-wavelength imaging.
DEEP-LEARNING-BASED REAL-TIME REMAINING SURGERY DURATION (RSD) ESTIMATION (US 20220296334 A1 ), Ghezelghich, et al. teaches building machine-learning-based surgical procedure analysis tools and, more specifically, to systems, devices and techniques for performing deep-learning-based real-time remaining surgery duration (RSD) estimations during a live surgical session of a surgical procedure based on endoscopy video feed.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
TOOL TRACKING SYSTEMS AND METHODS FOR IMAGE GUIDED SURGERY (US 20090088634 A1), Zhao, et al. teaches a tool tracking system is disclosed including a computer usable medium having computer readable program code to receive images of video frames from at least one camera and to perform image matching of a robotic instrument to determine video pose information of the robotic instrument within the images. The tool tracking system further includes computer readable program code to provide a state-space model of a sequence of states of corrected kinematics information for accurate pose information of the robotic instrument. The state-space model receives raw kinematics information of mechanical pose information and adaptively fuses the mechanical pose information and the video pose information together to generate the sequence of states of the corrected kinematics information for the robotic instrument. Additionally disclosed are methods for image guided surgery.
Robotic surgical systems with multi-modality imaging for performing surgical steps (US 11672614 B1), Roh, et al. teaches automated and robotic surgical procedures and specifically to apparatuses for performing robotic surgical procedures using automated disease detection by multiple-wavelength imaging.
DEEP-LEARNING-BASED REAL-TIME REMAINING SURGERY DURATION (RSD) ESTIMATION (US 20220296334 A1 ), Ghezelghich, et al. teaches building machine-learning-based surgical procedure analysis tools and, more specifically, to systems, devices and techniques for performing deep-learning-based real-time remaining surgery duration (RSD) estimations during a live surgical session of a surgical procedure based on endoscopy video feed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Amber Misiaszek whose telephone number is 571-270-1362. The examiner can normally be reached M-F 8:00-5:30, First Friday Off.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached on 571-270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AMBER A MISIASZEK/Primary Examiner, Art Unit 3682
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