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US 2022/0028059 A1Published application
Systems and Methods for Detecting Potential Malignancies
AssigneeIterative Scopes, Inc.
InventorsJonathan Ng, Sloane Allebes Phillips, Amit Ranade, Daniel Wang, Perikumar Mukundbhai Javia, Avi Walden, Austin Wang, Evan Wlodkowski, Samriddhi Dhakal
Life of this patent
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Abstract
One or more machine learning techniques can be used to identify locations of potential malignancies within images (e.g., video images) captured during a medical procedure, such as an endoscopic procedure. The images can be displayed, in real-time, on a display unit. The images can be displayed with a graphical overlay that isolates the identified locations of potential malignancies
Claims20
A data processing system for improving malignancy detection in individuals comprising:
- a computer-readable memory comprising computer-executable instructions;
- and
- at least one processor executing executable logic including at least one artificial neural network trained to identify visual representations of malignancies in an image, wherein when the at least one processor is executing the computer-executable instructions, the at least one processor carries out operations comprising:
- receiving, in real-time, spatially arranged image data associated with a plurality of images from an imaging device;
- generating a plurality of processed images by processing the spatially arranged image data through one or more data structures storing one or more portions of executable logic included in the artificial neural network to identify one or more pixels of the spatially arranged image data representing a location of a potential malignancy in an individual as the spatially arranged image data is received from the imaging device;
- causing, in real-time, a display unit to render the plurality of processed images, wherein:
- one or more processed images of the rendered plurality of processed images includes one or more graphical overlays generated by the at least one processor unless one or more of:
- a surgical tool is detected in the one or more processed images;
- or
- a image quality metric of the one or more processed images does not exceed a quality metric threshold;
- each of the one or more graphical overlays isolates one or more image locations;
- and
- each of the one or more image locations represents at least one pixel representing a location of a potential malignancy in the individual.
10 more elements
A method for improving malignancy detection in individuals comprising:
- receiving, in real-time, spatially arranged image data associated with a plurality of images from an imaging device;
- generating a plurality of processed images by processing the spatially arranged image data through one or more data structures storing one or more portions of executable logic included in an artificial neural network to identify one or more pixels of the spatially arranged image data representing a location of a potential malignancy in an individual as the spatially arranged image data is received from the imaging device;
- causing, in real-time, a display unit to render the plurality of processed images, wherein:
- one or more processed images of the rendered plurality of processed images includes one or more graphical overlays unless one or more of:
- a surgical tool is detected in the one or more processed images;
- or
- a image quality metric of the one or more processed images does not exceed a quality metric threshold;
- each of the one or more graphical overlays isolates one or more image locations;
- and
- each of the one or more image locations represents at least one pixel representing a location of a potential malignancy in the individual.
7 more elements
A system, comprising:
- a video capture card configured to receive, from an endoscopic processing unit, spatially arranged image data captured by an endoscopic imaging device of the endoscopic processing unit;
- a data processing system comprising:
- a display unit;
- a computer-readable memory comprising computer-executable instructions;
- and
- at least one processor executing executable logic including at least one artificial neural network trained to identify visual representations of malignancies in an image, wherein when the at least one processor is executing the computer-executable instructions, the at least one processor carries out operations comprising:
- receiving, in real-time, spatially arranged image data associated with a plurality of images from an imaging device;
- generating a plurality of processed images by processing the spatially arranged image data through one or more data structures storing one or more portions of executable logic included in the artificial neural network to identify one or more pixels of the spatially arranged image data representing a location of a potential malignancy in an individual as the spatially arranged image data is received from the imaging device;
- causing, in real-time, the display unit to render the plurality of processed images, wherein:
- one or more processed images of the rendered plurality of processed images includes one or more graphical overlays generated by the at least one processor unless one or more of:
- a surgical tool is detected in the one or more processed images;
- or
- a image quality metric of the one or more processed images does not exceed a quality metric threshold;
- each of the one or more graphical overlays isolates one or more image locations;
- and
- each of the one or more image locations represents at least one pixel representing a location of a potential malignancy in the individual
- a display switch configured to be communicatively coupled to the display unit, the data processing system, and the endoscopic processing unit, the display switch being further configured to allow displaying of either the plurality of processed images or a plurality of original images corresponding to the spatially arranged image data.
14 more elements
Dependencies are inferred from the claim text.