4 papers · 1 filter
IDRL: An Individual-Aware Multimodal Depression-Related Representation Learning Framework for Depression Diagnosis
Chongxiao Wang, Junjie Liang, Peng Cao +2
Depression is a severe mental disorder, and reliable identification plays a critical role in early intervention and treatment. Multimodal depression detection aims to improve diagn…
Visually-Guided Controllable Medical Image Generation via Fine-Grained Semantic Disentanglement
Xin Huang, Junjie Liang, Qingshan Hou +4
Medical image synthesis is crucial for alleviating data scarcity and privacy constraints. However, fine-tuning general text-to-image (T2I) models remains challenging, mainly due to…
BrainSTR: Spatio-Temporal Contrastive Learning for Interpretable Dynamic Brain Network Modeling
Guiliang Guo, Guangqi Wen, Lingwen Liu +6
Dynamic functional connectivity captures time-varying brain states for better neuropsychiatric diagnosis and spatio-temporal interpretability, i.e., identifying when discriminative…
SynMatch: Rethinking Consistency in Medical Image Segmentation with Sparse Annotations
Zhiqiang Shen, Peng Cao, Xiaoli Liu +2
Label scarcity remains a major challenge in deep learning-based medical image segmentation. Recent studies use strong-weak pseudo supervision to leverage unlabeled data. However, p…