后手术性胶质母细胞瘤分割：基于深度卷积神经网络的全自动管线开发与与现有模型的比较
图像与视频处理
2024-04-19 v1 计算机视觉与模式识别
摘要
准确评估肿瘤切除情况是脑胶质母细胞瘤管理的关键。我们开发了一个使用MRI扫描和神经网络的管线，用于后手术图像中的肿瘤亚区域和手术腔隆进行分割。我们的模型在准确分类切除范围方面表现突出，为临床医生评估治疗效果提供了有价值的工具。
引用
@article{arxiv.2404.11725,
title = {Postoperative glioblastoma segmentation: Development of a fully automated pipeline using deep convolutional neural networks and comparison with currently available models},
author = {Santiago Cepeda and Roberto Romero and Daniel Garcia-Perez and Guillermo Blasco and Luigi Tommaso Luppino and Samuel Kuttner and Ignacio Arrese and Ole Solheim and Live Eikenes and Anna Karlberg and Angel Perez-Nunez and Trinidad Escudero and Roberto Hornero and Rosario Sarabia},
journal= {arXiv preprint arXiv:2404.11725},
year = {2024}
}