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Usage of Artificial Intelligence in Gallbladder Segmentation to Diagnose Acute Cholecystitis

Author

Listed:
  • 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)

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.

Suggested Citation

  • Benjamin Wu & Yucheng Liu & Meng Jou Wu & Hiram Shaish & Hong Yun Ma, 2024. "Usage of Artificial Intelligence in Gallbladder Segmentation to Diagnose Acute Cholecystitis," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 55(2), pages 46766-46770, February.
    • Handle: RePEc:abf:journl:v:55:y:2024:i:2:p:46766-46770
    DOI: 10.26717/BJSTR.2024.55.008670
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