End-to-end deep learning for the diagnosis of pelvic and sacral tumors using non-enhanced MRI: a multi-center study

Abstract This study developed an end-to-end deep learning (DL) model using non-enhanced MRI to diagnose benign and malignant pelvic and sacral tumors (PSTs). Retrospective data from 835 patients across four hospitals were employed to train, validate, and test the models. Six diagnostic models with v...

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Bibliographic Details
Main Authors: Ping Yin, Ke Liu, Runrong Chen, Yang Liu, Lin Lu, Chao Sun, Ying Liu, Tianyu Zhang, Junwen Zhong, Weidao Chen, Ruize Yu, Dawei Wang, Xia Liu, Nan Hong
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:npj Precision Oncology
Online Access:https://doi.org/10.1038/s41698-025-01077-3
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