5 papers
Landmarks Are Alike Yet Distinct: Harnessing Similarity and Individuality for One-Shot Medical Landmark Detection
Xu He, Zhen Huang, Qingsong Yao +2
Landmark detection plays a crucial role in medical imaging applications such as disease diagnosis, bone age estimation, and therapy planning. However, training models for detecting…
Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
Chenxu Wu, Qingpeng Kong, Zihang Jiang +1
Magnetic Resonance Imaging (MRI), including diffusion MRI (dMRI), serves as a ``microscope'' for anatomical structures and routinely mitigates the influence of low signal-to-noise…
Hi-End-MAE: Hierarchical encoder-driven masked autoencoders are stronger vision learners for medical image segmentation
Fenghe Tang, Qingsong Yao, Wenxin Ma +3
Medical image segmentation remains a formidable challenge due to the label scarcity. Pre-training Vision Transformer (ViT) through masked image modeling (MIM) on large-scale unlabe…
Towards Accurate Unified Anomaly Segmentation
Wenxin Ma, Qingsong Yao, Xiang Zhang +3
Unsupervised anomaly detection (UAD) from images strives to model normal data distributions, creating discriminative representations to distinguish and precisely localize anomalies…
FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models
Ruinan Jin, Zikang Xu, Yuan Zhong +4
The advent of foundation models (FMs) in healthcare offers unprecedented opportunities to enhance medical diagnostics through automated classification and segmentation tasks. Howev…