基于多模态表示学习的阿尔兹海默症诊断算法  

Multimodal Representation Learning for Alzheimer’s Disease Diagnosis

作　　者：樊连玺 刘彦北[2,3] 王雯 耿磊[2] 吴骏[1] 张芳[2] 肖志涛[2] FAN Lian-xi;LIU Yan-bei;WANG Wen;GENG Lei;WU Jun;ZHANG Fang;XIAO Zhi-tao(School of Electronics and Information Engineering,Tiangong University,Tianjin 300387,China;School of Life Sciences,Tiangong University,Tianjin 300387,China;Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems,Tianjin 300387,China)

机构地区：[1]天津工业大学电子与信息工程学院,天津300387 [2]天津工业大学生命科学学院,天津300387 [3]天津光电检测技术与系统重点实验室,天津300387

出　　处：《计算机科学》2021年第10期107-113,共7页Computer Science

基　　金：国家自然基金项目(61901297);天津市科学技术重大专项与工程(17ZXSCSY00060)。

摘　　要：阿尔茨海默症是一种典型的涉及多种致病因素的神经系统退行性疾病。然而,阿尔茨海默症的病因尚不明确,病程不可逆转,且无治愈方法,因此其早期诊断和治疗一直是人们关注的重点。受试者的神经影像数据对于该疾病的诊断具有重要的辅助作用,而结合多个模态的数据可进一步提高诊断效果。目前,联合该疾病的多模态数据进行辅助诊断逐渐成为一个新兴的研究领域。在此提出了一种基于自编码器的多模态表示学习方法,用于阿尔茨海默症的诊断。首先将多个模态的数据进行初步融合,得到初级的共同表示;然后将其送入自编码器网络,学习隐空间中的共同表示;最后对隐空间中的共同表示进行分类,得到疾病的诊断结果。在国际公开ADNI数据集上,所提算法对患病和健康受试者的诊断准确率达到88.9%,与同类算法相比取得了最好的诊断效果。实验结果验证了所提算法对阿尔茨海默症诊断的有效性。Alzheimer’s disease(AD)is a complex neurodegenerative disease involving a variety of pathogenic factors.So far,the cause of Alzheimer’s disease is not clear,the course of the disease is irreversible,and there is no cure.Its early diagnosis and treatment have always been the focus of attention.The neuroimaging data of subjects has an important auxiliary role in the diagnosis of this disease,and the combination of multimodal data can further improve the diagnostic effect.At present,the multimodal data representation learning of the disease has gradually become an emerging research field,which has attracted wide attention from researchers.An autoencoder based multimodal representation learning method for Alzheimer’s disease diagnosis is proposed.Firstly,the multimodal data are initially fused to obtain the primary common representation.Then,it is input into the autoencoder network to learn the final common representation in latent space.Finally,the common representation in latent space is classified to obtain the disease result.The proposed method,which achieves the best diagnostic results compared with comparison algorithms,has an accuracy of 88.9%in the classification of AD and healthy subjects in the ADNI dataset.Extensive experimental results verify its effectiveness.

关 键 词：阿尔兹海默症 疾病诊断 多模态融合 表示学习 自编码器网络 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]