Abstract: A system for automatically analyzing a video recording of a colonoscopy includes a processor and memory storing instructions, which when executed by the processor, cause the processor to receive the video recording of the colonoscopy performed on the colon and detect informative frames in the video recording. A frame is informative if the clarity of the frame is above a threshold or if the frame includes clinically relevant information about the colon. The instructions cause the processor to generate scores indicating severity levels of a disease for a plurality of the informative frames, estimate locations of the plurality of the informative frames in the colon, and generate an output indicating a distribution of the scores over one or more segments of the colon by combining the scores generated for the plurality of the informative frames and the estimated locations of the plurality of the informative frames in the colon.

Abstract: A computer-automated method is presented for segmenting image data for an organ of a subject, where the organ is a tubular structure. The method includes: receiving image data representing a volume of the subject, such that the image data includes the organ; generating a centerline through the organ; determining location of an outer wall of the tube within the image data, where the location of the inner wall is determined using the centerline; determining location of an outer wall of the tube within the image data, where the location of the outer wall is determined using the inner wall; and computing a measure of the organ from the image data.

Abstract: A system for automatically analyzing a video recording of a colonoscopy includes a processor and memory storing instructions, which when executed by the processor, cause the processor to receive the video recording of the colonoscopy performed on the colon and detect informative frames in the video recording. A frame is informative if the clarity of the frame is above a threshold or if the frame includes clinically relevant information about the colon. The instructions cause the processor to generate scores indicating severity levels of a disease for a plurality of the informative frames, estimate locations of the plurality of the informative frames in the colon, and generate an output indicating a distribution of the scores over one or more segments of the colon by combining the scores generated for the plurality of the informative frames and the estimated locations of the plurality of the informative frames in the colon.

Abstract: A computer-automated method is presented for segmenting image data for an organ of a subject, where the organ is a tubular structure. The method includes: receiving image data representing a volume of the subject, such that the image data includes the organ; generating a centerline through the organ; determining location of an outer wall of the tube within the image data, where the location of the inner wall is determined using the centerline; determining location of an outer wall of the tube within the image data, where the location of the outer wall is determined using the inner wall; and computing a measure of the organ from the image data.