4 accepted papers
Analyzing functional connectivity patterns from resting-state functional magnetic resonance imaging (fMRI) requires unraveling its interrelations across spatial, temporal, and frequency domains. To comprehensively analyze four-dimensional (4D) fMRI data, we propose the Spatiotemporal Frequency Graph…
Multimodal emotion recognition (MER) aims to identify emotions by utilizing affective information from multiple modalities. Due to the inherent disparities among these heterogeneous modalities, there is a large modality gap in their representations, leading to the challenge of fusing multiple modali…
Large Vision Model (LVM) has recently demonstrated great potential for medical imaging tasks, potentially enabling image enhancement for sparse-view Cone-Beam Computed Tomography (CBCT), despite requiring a substantial amount of data for training. Meanwhile, Deep Image Prior (DIP) effectively guides…
Semi-supervised learning (SSL) algorithms have attracted much attentions in medical image segmentation by leveraging unlabeled data, which challenge in acquiring massive pixel-wise annotated samples. However, most of the existing SSLs neglected the geometric shape constraint in object, leading to un…