Cargando…
Decomposition-Based Correlation Learning for Multi-Modal MRI-Based Classification of Neuropsychiatric Disorders
Multi-modal magnetic resonance imaging (MRI) is widely used for diagnosing brain disease in clinical practice. However, the high-dimensionality of MRI images is challenging when training a convolution neural network. In addition, utilizing multiple MRI modalities jointly is even more challenging. We...
Autores principales: | Liu, Liangliang, Chang, Jing, Wang, Ying, Liang, Gongbo, Wang, Yu-Ping, Zhang, Hui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9174798/ https://www.ncbi.nlm.nih.gov/pubmed/35692429 http://dx.doi.org/10.3389/fnins.2022.832276 |
Ejemplares similares
-
MRI-Based Classification of Neuropsychiatric Systemic Lupus Erythematosus Patients With Self-Supervised Contrastive Learning
por: Inglese, Francesca, et al.
Publicado: (2022) -
Identifying Early Mild Cognitive Impairment by Multi-Modality MRI-Based Deep Learning
por: Kang, Li, et al.
Publicado: (2020) -
Editorial: Multi-dimensional characterization of neuropsychiatric disorders
por: Wang, Peng, et al.
Publicado: (2022) -
Emotion recognition based on multi-modal physiological signals and transfer learning
por: Fu, Zhongzheng, et al.
Publicado: (2022) -
Multi-modal intermediate integrative methods in neuropsychiatric disorders: A review
por: Wang, Yanlin, et al.
Publicado: (2022)