计算机与数字工程2024，Vol.52Issue(1)：150-155,6.DOI:10.3969/j.issn.1672-9722.2024.01.024
融合多模态多尺度磁共振成像的脑胶质瘤分割
Brain Glioma Segmentation with Multi-modal and Multi-scale Magnetic Resonance Imaging
摘要
Abstract
To achieve precise segmentation of small target regions of glioma,a multi-modal and multi-scale MRI glioma seg-mentation model is proposed.The image features of each modality are obtained through the multi-modal feature extraction module,which enhances the reusability of the feature information by the network.The multi-scale feature fusion module is used to learn key features at different scales,and improve the feature recognition ability of the network for small target glioma regions.A weighted hy-brid loss function is used to address the class imbalance problem.The proposed model is tested on the BraTS(brain tumor segmenta-tion)2019 dataset,where the Dice scores of the whole tumor,tumor core,and enhancing tumor are 0.857,0.869 and 0.878,and Hausdorff distances are 2.543,1.583 and 1.526,respectively.The experimental results show that the model can effectively improve the segmentation accuracy of small target regions of glioma.关键词
脑胶质瘤/小目标分割/多模态特征/多尺度融合Key words
brain glioma/small object segmentation/multi-modal features/multi-scale fusion分类
医药卫生引用本文复制引用
裴玉瑶,王常青,吴茜..融合多模态多尺度磁共振成像的脑胶质瘤分割[J].计算机与数字工程,2024,52(1):150-155,6.基金项目
国家自然科学基金青年项目(编号:62001005) （编号:62001005）
安徽高校科学研究项目(编号:2022AH050660)资助. （编号:2022AH050660）
