University of Michigan

Northern Arizona University

Sayedmohammadreza Soroushmehr

Kayvan Najarian

Kevin R Ward

Jonathan Gryak

Fatemeh Afghah

Brahmajee Kartik Nallamothu

Abolfazl Razi

Ryan W Stidham

Heming Yao

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.

Automated anatomic and regional location of disease features in colonoscopy videos

Implementations of a system for determining the relevancy of a plurality of alarms may include: a plurality of sensors configured to be coupled to a patient, wherein the plurality of sensors is configured to gather physiological data, a medical monitoring device coupled to the plurality of sensors through a telecommunication channel, and wherein the medical monitoring device is configured to determine a physiological state of the patient using the physiological data. The medical monitoring device may be further configured to issue a plurality of alarm states, and a processing unit coupled to the medical monitoring device through a telecommunication channel, is then configured to evaluate the plurality of alarm states, determine the relevancy of each alarm state of the plurality of alarm states, and issue one or more alarms corresponding with each relevant alarm state to a computing device associated with a user.

False alarm reduction systems and related methods

A system analyzes angiogram image data, including video data, in order to extract vasculature information. Advanced image processing and machine learning techniques are used in pre-processing, frame selection, and vasculature segmentation to remove classes of artifacts from angiogram videos, and specifically from frames selected as having a sufficient amount of image data. From segmentation, accurate vasculature diameters are calculated, and, in some examples, stenoses and/or the extent of stenosis is automatically determined and displayed.

Automated analysis of vasculature in coronary angiograms

Growing community of inventors

Ann Arbor, MI, United States of America

Sayedmohammadreza Soroushmehr