Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma

Abstract Objective This study aims to compare the feasibility and effectiveness of automatic deep learning network and radiomics models in differentiating low tumor stroma ratio (TSR) from high TSR in pancreatic ductal adenocarcinoma (PDAC). Methods A retrospective analysis was conducted on a total...

وصف كامل

التفاصيل البيبلوغرافية

المؤلفون الرئيسيون:	Hongfan Liao, Jiang Yuan, Chunhua Liu, Jiao Zhang, Yaying Yang, Hongwei Liang, Song Jiang, Shanxiong Chen, Yongmei Li, Yanbing Liu
التنسيق:	Artigo
اللغة:	Inglês
منشور في:	SpringerOpen 2023-12-01
سلاسل:	Insights into Imaging
الموضوعات:	Machine learning Radiomics Deep learning Tumor stroma ratio Pancreatic ductal adenocarcinoma
الوصول للمادة أونلاين:	https://doi.org/10.1186/s13244-023-01553-z
الوسوم:	إضافة وسم لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!