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-  2018 

基于稀疏表示体系的原发性脑部淋巴瘤和胶质母细胞瘤图像鉴别

DOI: doi:10.7507/1001-5515.201705061

Keywords: 肿瘤图像鉴别, 稀疏表示, 特征提取, 特征选择

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Abstract:

临床上原发性脑部淋巴瘤(PCNSL)和胶质母细胞瘤(GBM)的治疗方案存在很大差异,因此治疗前对二者的精确鉴别具有重要临床价值。本文提出一套基于稀疏表示体系的肿瘤自动鉴别方法,利用 PCNSL 和 GBM T1 加权磁共振成像(MRI)图像纹理细节信息的差异鉴别这两种肿瘤。首先,基于影像组学的思想,设计一种基于字典学习和稀疏表示的肿瘤纹理特征提取方法,将不同体积、不同形状的肿瘤区域转化为 968 维纹理特征;其次,针对提取特征存在的冗余问题,建立迭代稀疏表示方法选择少数高稳定性高分辨力的特征;最后,将选择的关键特征送入稀疏表示分类器(SRC)分类。利用十折法对数据集进行交叉验证,鉴别结果的准确率为 96.36%,敏感度为 96.30%,特异性为 96.43%。实验结果表明,本文方法不仅能够有效地鉴别 PCNSL 和 GBM,还避免了使用先进 MRI 鉴别肿瘤时存在的参数提取问题,在实际应用中具有较强的鲁棒性

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