VIDEO-BASED ANALYSIS OF STAPLING EVENTS DURING A SURGICAL PROCEDURE USING MACHINE LEARNING

An analysis system trains a machine learning model to detect stapling events from a video of a surgical procedure. The machine learning model detects times when stapling events occur as well as one or more characteristics of each stapling event such as length of staples, clamping time, or other char...

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Bibliographische Detailangaben
Hauptverfasser:	GOEL, Varun Kejriwal, STURGEON, Darrick Tyler, BARKER, Jocelyn, ARONHALT, Taylor W
Format:	Patent
Sprache:	eng ; fre ; ger
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DIAGNOSIS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE PHYSICS SURGERY
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Beschreibung
Zusammenfassung:	An analysis system trains a machine learning model to detect stapling events from a video of a surgical procedure. The machine learning model detects times when stapling events occur as well as one or more characteristics of each stapling event such as length of staples, clamping time, or other characteristics. The machine learning model is trained on videos of surgical procedures identifying when stapling events occurred through a learning process. The machine learning model may be applied to an input video to detect a sequence of stapler events. Stapler event sequences may furthermore be analyzed and/or aggregated to generate various analytical data relating to the surgical procedures for applications such as inventor management, performance evaluation, or predicting patient outcomes.