A deep learning-based semiautomated workflow for triaging follow-up MR scans in treated nasopharyngeal carcinoma

A deep learning-based semiautomated workflow for triaging follow-up MR scans in treated nasopharyngeal carcinoma

Summary: It is imperative to optimally utilize virtues and obviate defects of fully automated analysis and expert knowledge in new paradigms of healthcare. We present a deep learning-based semiautomated workflow (RAINMAN) with 12,809 follow-up scans among 2,172 patients with treated nasopharyngeal c...

Full description

Bibliographic Details
Main Authors: Ying-Ying Huang, Yi-Shu Deng, Yang Liu, Meng-Yun Qiang, Wen-Ze Qiu, Wei-Xiong Xia, Bing-Zhong Jing, Chen-Yang Feng, Hao-Hua Chen, Xun Cao, Jia-Yu Zhou, Hao-Yang Huang, Ze-Jiang Zhan, Ying Deng, Lin-Quan Tang, Hai-Qiang Mai, Ying Sun, Chuan-Miao Xie, Xiang Guo, Liang-Ru Ke, Xing Lv, Chao-Feng Li
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:iScience
Subjects:
Health technology
Applied computing
Online Access:http://www.sciencedirect.com/science/article/pii/S2589004223024240

Internet

http://www.sciencedirect.com/science/article/pii/S2589004223024240

Similar Items