基本事实
胶质瘤
磁共振成像
计算机科学
人工智能
计算机视觉
核磁共振
自然语言处理
物理
医学
放射科
癌症研究
作者
Shiwen Cao,Zhaoyu Hu,Xuan Xie,Yuanyuan Wang,Jinhua Yu,Bojie Yang,Zhifeng Shi,Guoqing Wu
标识
DOI:10.1016/j.compbiomed.2024.108968
摘要
Since the 2016 WHO guidelines, glioma diagnosis has entered an era of integrated diagnosis, combining tissue pathology and molecular pathology. The WHO has focused on promoting the application of molecular diagnosis in the classification of central nervous system tumors. Genetic information such as IDH1 and 1p/19q are important molecular markers, and pathological grading is also a key clinical indicator. However, obtaining genetic pathology labels is more costly than conventional MRI images, resulting in a large number of missing labels in realistic modeling.
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