Lele Chen, Yue Wu, Adora M. DSouza, Anas Z. Abidin, Axel Wismuller...
TL;DR本研究提出了基于 3D CNN 的新型分割网络对 Glioma 进行自动分割,该方法利用 MRI 数据帮助病灶分割,分类准确率较高,是一种有效和高效的病灶分割方法,可以帮助研究和评估 Glioma 的治疗效果。
Abstract
glioma is one of the most common and aggressive types of primary brain tumors. The accurate segmentation of subcortical brain structures is crucial to the study of gliomas in that it helps the monitoring of the p