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An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling
Blanca Inigo, Yiqing Shen, Benjamin D. Killeen +4
Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteoporosis. Yet, they often remain undiagnosed. Opportunistic screening, which involves…
Memorizing SAM: 3D Medical Segment Anything Model with Memorizing Transformer
Xinyuan Shao, Yiqing Shen, Mathias Unberath
Segment Anything Models (SAMs) have gained increasing attention in medical image analysis due to their zero-shot generalization capability in segmenting objects of unseen classes a…
Promptable Counterfactual Diffusion Model for Unified Brain Tumor Segmentation and Generation with MRIs
Yiqing Shen, Guannan He, Mathias Unberath
Brain tumor analysis in Magnetic Resonance Imaging (MRI) is crucial for accurate diagnosis and treatment planning. However, the task remains challenging due to the complexity and v…
FastSAM-3DSlicer: A 3D-Slicer Extension for 3D Volumetric Segment Anything Model with Uncertainty Quantification
Yiqing Shen, Xinyuan Shao, Blanca Inigo Romillo +2
Accurate segmentation of anatomical structures and pathological regions in medical images is crucial for diagnosis, treatment planning, and disease monitoring. While the Segment An…
FastSAM3D: An Efficient Segment Anything Model for 3D Volumetric Medical Images
Yiqing Shen, Jingxing Li, Xinyuan Shao +4
Segment anything models (SAMs) are gaining attention for their zero-shot generalization capability in segmenting objects of unseen classes and in unseen domains when properly promp…