62 citations · 226 across the 10 of their papers we have counts for
9 papers · 1 filter
KG-CMI: Knowledge graph enhanced cross-Mamba interaction for medical visual question answering
Xianyao Zheng, Hong Yu, Hui Cui +7
Medical visual question answering (Med-VQA) is a crucial multimodal task in clinical decision support and telemedicine. Recent methods fail to fully leverage domain-specific medica…
CMI-MTL: Cross-Mamba interaction based multi-task learning for medical visual question answering
Qiangguo Jin, Xianyao Zheng, Hui Cui +7
Medical visual question answering (Med-VQA) is a crucial multimodal task in clinical decision support and telemedicine. Recent self-attention based methods struggle to effectively…
ERSR: An Ellipse-constrained pseudo-label refinement and symmetric regularization framework for semi-supervised fetal head segmentation in ultrasound images
Linkuan Zhou, Zhexin Chen, Yufei Shen +9
Automated segmentation of the fetal head in ultrasound images is critical for prenatal monitoring. However, achieving robust segmentation remains challenging due to the poor qualit…
Iterative pseudo-labeling based adaptive copy-paste supervision for semi-supervised tumor segmentation
Qiangguo Jin, Hui Cui, Junbo Wang +7
Semi-supervised learning (SSL) has attracted considerable attention in medical image processing. The latest SSL methods use a combination of consistency regularization and pseudo-l…
Location embedding based pairwise distance learning for fine-grained diagnosis of urinary stones
Qiangguo Jin, Jiapeng Huang, Changming Sun +8
The precise diagnosis of urinary stones is crucial for devising effective treatment strategies. The diagnostic process, however, is often complicated by the low contrast between st…
Inter- and intra-uncertainty based feature aggregation model for semi-supervised histopathology image segmentation
Qiangguo Jin, Hui Cui, Changming Sun +5
Acquiring pixel-level annotations is often limited in applications such as histology studies that require domain expertise. Various semi-supervised learning approaches have been de…