An integrative deep learning model based on dual-mode ultrasound for diagnosing gallbladder polyps.

ABSTRACT:

Objectives

The aim of this study was to develop an artificial intelligence model to automatically differentiate between non-neoplastic and neoplastic gallbladder polyps, while also distinguishing benign from malignant polyps.

Materials and methods

Patients with gallbladder polyps who underwent cholecystectomy from January 2022 to June 2023 were recruited from two hospitals retrospectively. Conventional ultrasound findings and clinical characteristics of patients before cholecystectomy were acquired. Ultrasound image blocks of gallbladder lesions were automatically segmented by the Unet network for diagnosis. A fusion deep learning model based on dual-mode ultrasound (grey-scale ultrasound and colour Doppler flow imaging) was established to diagnose gallbladder polyps and val

SUBMITTER: Tang C 

PROVIDER: S-EPMC12864583 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature