19 papers
Automated Report-Derived Oncology VQA Benchmark for Evaluating Vision-Language Models on 3D Medical Imaging
Bo Liu, Hanxue Gu, Xiangru Li +6
Evaluating vision-language models (VLMs) on medical images requires benchmarks that are clinically grounded, scalable, and controlled for evaluation confounds. Existing public benc…
LegSegNet: A Public Deep Learning System for Lower Extremity CT Tissue Segmentation and Quantification
Yuwen Chen, Yaqian Chen, Roy Colglazier +4
Lower extremity computed tomography (CT) contains clinically relevant information for body composition analysis, sarcopenia assessment, and musculoskeletal disease monitoring, but…
Fully Automated Deep Learning Based Glenoid Bone Loss Measurement and Severity Stratification on 3D CT in Shoulder Instability
Zhonghao Liu, Hanxue Gu, Qihang Li +4
To develop and validate a fully automated, deep-learning pipeline for measuring glenoid bone loss on 3D CT scans using linear-based, en-face view, and best-circle method. Shoulder…
ContourDiff: Unpaired Medical Image Translation with Structural Consistency
Yuwen Chen, Nicholas Konz, Hanxue Gu +5
Accurately translating medical images between different modalities, such as Computed Tomography (CT) to Magnetic Resonance Imaging (MRI), has numerous downstream clinical and machi…
Automated Muscle and Fat Segmentation in Computed Tomography for Comprehensive Body Composition Analysis
Yaqian Chen, Hanxue Gu, Yuwen Chen +7
Body composition assessment using CT images can potentially be used for a number of clinical applications, including the prognostication of cardiovascular outcomes, evaluation of m…
SAMora: Enhancing SAM through Hierarchical Self-Supervised Pre-Training for Medical Images
Shuhang Chen, Hangjie Yuan, Pengwei Liu +3
The Segment Anything Model (SAM) has demonstrated significant potential in medical image segmentation. Yet, its performance is limited when only a small amount of labeled data is a…