干旱区生态环境知识资源中心(Arid): Multi input-Multi output 3D CNN for dementia severity assessment with incomplete multimodal data

Arid

DOI	10.1016/j.artmed.2024.102774
	Multi input-Multi output 3D CNN for dementia severity assessment with incomplete multimodal data
	Gravina, Michela; Garcia-Pedrero, Angel; Gonzalo-Martin, Consuelo; Sansone, Carlo; Soda, Paolo
通讯作者	Gonzalo-Martín, C
来源期刊	ARTIFICIAL INTELLIGENCE IN MEDICINE
ISSN	0933-3657
EISSN	1873-2860
出版年	2024
卷号	149
英文摘要	Alzheimer's Disease is the most common cause of dementia, whose progression spans in different stages, from very mild cognitive impairment to mild and severe conditions. In clinical trials, Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) are mostly used for the early diagnosis of neurodegenerative disorders since they provide volumetric and metabolic function information of the brain, respectively. In recent years, Deep Learning (DL) has been employed in medical imaging with promising results. Moreover, the use of the deep neural networks, especially Convolutional Neural Networks (CNNs), has also enabled the development of DL-based solutions in domains characterized by the need of leveraging information coming from multiple data sources, raising the Multimodal Deep Learning (MDL). In this paper, we conduct a systematic analysis of MDL approaches for dementia severity assessment exploiting MRI and PET scans. We propose a Multi Input- Multi Output 3D CNN whose training iterations change according to the characteristic of the input as it is able to handle incomplete acquisitions, in which one image modality is missed. Experiments performed on OASIS-3 dataset show the satisfactory results of the implemented network, which outperforms approaches exploiting both single image modality and different MDL fusion techniques.
英文关键词	Convolutional neural networks Magnetic resonance images Positron emission tomography Multimodal deep learning
类型	Article
语种	英语
开放获取类型	Green Published, hybrid
收录类别	SCI-E
WOS记录号	WOS:001178872000001
WOS关键词	ALZHEIMERS-DISEASE ; EARLY-DIAGNOSIS
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Biomedical ; Medical Informatics
WOS研究方向	Computer Science ; Engineering ; Medical Informatics
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/402958
推荐引用方式 GB/T 7714	Gravina, Michela,Garcia-Pedrero, Angel,Gonzalo-Martin, Consuelo,et al. Multi input-Multi output 3D CNN for dementia severity assessment with incomplete multimodal data[J],2024,149.
APA	Gravina, Michela,Garcia-Pedrero, Angel,Gonzalo-Martin, Consuelo,Sansone, Carlo,&Soda, Paolo.(2024).Multi input-Multi output 3D CNN for dementia severity assessment with incomplete multimodal data.ARTIFICIAL INTELLIGENCE IN MEDICINE,149.
MLA	Gravina, Michela,et al."Multi input-Multi output 3D CNN for dementia severity assessment with incomplete multimodal data".ARTIFICIAL INTELLIGENCE IN MEDICINE 149(2024).