Usage of Artificial Intelligence in Gallbladder Segmentation to Diagnose Acute Cholecystitis

Benjamin Wu, Yucheng Liu, Meng Jou Wu, Hiram Shaish and Hong Yun Ma
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Benjamin Wu: NYU Stern School of Business, New York University, USA
Yucheng Liu: Department of Radiology, Division of physics, Columbia University Irving Medical Center, USA
Meng Jou Wu: Department of Radiology, Division of physics, Columbia University Irving Medical Center, USA
Hiram Shaish: Department of Radiology, Division of Body, Columbia University Irving Medical Center, USA
Hong Yun Ma: Department of Radiology, Division of Body, Columbia University Irving Medical Center, USA

Biomedical Journal of Scientific & Technical Research, 2024, vol. 55, issue 2, 46766-46770

Abstract: Acute Cholecystitis is a sudden inflammation of the gallbladder that affects hundreds of thousands of people per year. Though a common condition, methods of diagnosis still underperform modern standards of medicine. As such, there has been a demand to incorporate new innovations in the diagnostic process. In this study, a modified U-Net was trained to automatically segment gallbladder ultrasound images.

Keywords: Journals on Medical Drug and Therapeutics; Journals on Emergency Medicine; Physical Medicine and Rehabilitation; Journals on Infectious Diseases Addiction Science and Clinical Pathology; Open Access Clinical and Medical Journal; Journals on Biomedical Science; List of Open Access Medical Journal; Journals on Biomedical Engineering; Open Access Medical Journal; Biomedical Science Articles; Journal of Scientific and Technical Research (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:abf:journl:v:55:y:2024:i:2:p:46766-46770

DOI: 10.26717/BJSTR.2024.55.008670

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