Real-time artificial intelligence-assisted detection and segmentation of nasopharyngeal carcinoma using multimodal endoscopic data: a multi-center, prospective study.

ABSTRACT:

Background

Nasopharyngeal carcinoma (NPC) is a common malignancy in southern China, and often underdiagnosed due to reliance on physician expertise. Artificial intelligence (AI) can enhance diagnostic accuracy and efficiency using large datasets and advanced algorithms.

Methods

Nasal endoscopy videos with white light imaging (WLI) and narrow-band imaging (NBI) modes from 707 patients treated at one center in China from June 2020 to December 2022 were prospectively collected. A total of 8816 frames were obtained through standardized data procedures. Nasopharyngeal Carcinoma Diagnosis Segmentation Network Framework (NPC-SDNet) was developed and internally tested based on these frames. Two hundred frames were randomly selected to compare the diagnostic performance between NPC-S

SUBMITTER: He R 

PROVIDER: S-EPMC11871492 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature