2 citations · 3 across the 12 of their papers we have counts for
8 papers · 1 filter
Universality Reconsidered: Rethinking the Validation of Foundation Models for General-Purpose 3D Medical Segmentation
Yichi Zhang, Le Xue, Feiyang Xiao +6
Foundation models have emerged as a transformative paradigm in 3D medical imaging, with the promise of unified quantitative analysis across diverse targets and imaging modalities.…
Structure-aware Semantic Discrepancy and Consistency for 3D Medical Image Self-supervised Learning
Tan Pan, Zhaorui Tan, Kaiyu Guo +6
3D medical image self-supervised learning (mSSL) holds great promise for medical analysis. Effectively supporting broader applications requires considering anatomical structure var…
SegAnyPET: Universal Promptable Segmentation from Positron Emission Tomography Images
Yichi Zhang, Le Xue, Wenbo Zhang +5
Positron Emission Tomography (PET) is a powerful molecular imaging tool that plays a crucial role in modern medical diagnostics by visualizing radio-tracer distribution to reveal p…
Aneumo: A Large-Scale Comprehensive Synthetic Dataset of Aneurysm Hemodynamics
Xigui Li, Yuanye Zhou, Feiyang Xiao +10
Intracranial aneurysm (IA) is a common cerebrovascular disease that is usually asymptomatic but may cause severe subarachnoid hemorrhage (SAH) if ruptured. Although clinical practi…
Towards a Universal 3D Medical Multi-modality Generalization via Learning Personalized Invariant Representation
Zhaorui Tan, Xi Yang, Tan Pan +8
Variations in medical imaging modalities and individual anatomical differences pose challenges to cross-modality generalization in multi-modal tasks. Existing methods often concent…
SemiSAM: Enhancing Semi-Supervised Medical Image Segmentation via SAM-Assisted Consistency Regularization
Yichi Zhang, Jin Yang, Yuchen Liu +2
Semi-supervised learning has attracted much attention due to its less dependence on acquiring abundant annotations from experts compared to fully supervised methods, which is espec…