A novel artificial intelligence segmentation model for early diagnosis of bladder tumors.
Journal:
Abdominal radiology (New York)
Published Date:
Dec 30, 2024
Abstract
OBJECTIVE: Despite cystoscopy plays an important role in bladder tumors diagnosis, it often falls short in flat cancerous tissue and minuscule satellite lesions. It can easily lead to a missed diagnosis by the urologist, which can lead to a swift tumor regrowth following transurethral resection of the bladder tumor (TURBT). Therefore, we developed a deep learning-based intelligent diagnosis system for early bladder cancer to improve the identification rate of early bladder tumors.
