Deep learning feature-based model for predicting lymphovascular invasion in urothelial carcinoma of bladder using CT images

Deep learning feature-based model for predicting lymphovascular invasion in urothelial carcinoma of bladder using CT images

Abstract Objectives Lymphovascular invasion significantly impacts the prognosis of urothelial carcinoma of the bladder. Traditional lymphovascular invasion detection methods are time-consuming and costly. This study aims to develop a deep learning-based model to preoperatively predict lymphovascular...

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Main Authors: Bangxin Xiao, Yang Lv, Canjie Peng, Zongjie Wei, Qiao Xv, Fajin Lv, Qing Jiang, Huayun Liu, Feng Li, Yingjie Xv, Quanhao He, Mingzhao Xiao
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:Insights into Imaging
Subjects:
Urothelial carcinoma of the bladder
Lymphovascular invasion
Deep learning model
Stacking learning model
Multicenter retrospective study
Online Access:https://doi.org/10.1186/s13244-025-01988-6
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https://doi.org/10.1186/s13244-025-01988-6

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