5 papers
Reduce, Then Encode: Multiscale Volumetric Reduction for 2D Foundation Models in Brain MRI
Dexuan Ding, Yuankai Qi, Bogong Wang +2
Pretrained 2D foundation models offer a practical alternative to dedicated 3D pretraining for brain structural magnetic resonance imaging (sMRI), but their use on volumetric data r…
Recurrent Contrastive Learning for Imbalanced Medical Image Classification
Zhiyuan Zhu, Xinling Meng, Junxuan Yu +15
Medical image classification often suffers from class imbalance due to the inherent disparities in disease incidence. Existing approaches, such as class resampling and loss reweigh…
ProgFormer: Hierarchical Voxel Diffusion Transformer for Longitudinal Brain MRI Prediction
Dexuan Ding, Yuankai Qi, Luping Zhou +3
Predicting future structural MRI of a brain is challenging because longitudinal changes are often subtle and confined to specific anatomical regions, while most subject-specific br…
Hierarchical Text-Guided Brain Tumor Segmentation via Sub-Region-Aware Prompts
Bahram Mohammadi, Ta Duc Huy, Afrouz Sheikholeslami +8
Brain tumor segmentation remains challenging because the three standard sub-regions, i.e., whole tumor (WT), tumor core (TC), and enhancing tumor (ET), often exhibit ambiguous visu…
Imbalanced Medical Image Segmentation with Pixel-dependent Noisy Labels
Erjian Guo, Zicheng Wang, Zhen Zhao +1
Accurate medical image segmentation is often hindered by noisy labels in training data, due to the challenges of annotating medical images. Prior research works addressing noisy la…