Decomposing 3D Neuroimaging into 2+1D Processing for Schizophrenia Recognition. (arXiv:2211.11557v2 [eess.IV] UPDATED)

Deep learning has been successfully applied to recognizing both natural
images and medical images. However, there remains a gap in recognizing 3D
neuroimaging data, especially for psychiatric diseases such as schizophrenia
and depression that have no visible alteration in specific slices. In this
study, we propose to process the 3D data by a 2+1D framework so that we can
exploit the powerful deep 2D Convolutional Neural Network (CNN) networks
pre-trained on the huge ImageNet dataset for 3D neuroimaging recognition.
Specifically, …

arxiv neuroimaging processing schizophrenia