38 citations · 67 across the 53 of their papers we have counts for
15 papers · 1 filter
Learning Segmentation from Radiology Reports
Pedro R. A. S. Bassi, Wenxuan Li, Jieneng Chen +8
Tumor segmentation in CT scans is key for diagnosis, surgery, and prognosis, yet segmentation masks are scarce because their creation requires time and expertise. Public abdominal…
PanTS: The Pancreatic Tumor Segmentation Dataset
Wenxuan Li, Xinze Zhou, Qi Chen +15
PanTS is a large-scale, multi-institutional dataset curated to advance research in pancreatic CT analysis. It contains 36,390 CT scans from 145 medical centers, with expert-validat…
ShapeKit
Junqi Liu, Dongli He, Wenxuan Li +3
In this paper, we present a practical approach to improve anatomical shape accuracy in whole-body medical segmentation. Our analysis shows that a shape-focused toolkit can enhance…
Are Pixel-Wise Metrics Reliable for Sparse-View Computed Tomography Reconstruction?
Tianyu Lin, Xinran Li, Chuntung Zhuang +5
Widely adopted evaluation metrics for sparse-view CT reconstruction--such as Structural Similarity Index Measure and Peak Signal-to-Noise Ratio--prioritize pixel-wise fidelity but…
How Well Do Supervised 3D Models Transfer to Medical Imaging Tasks?
Wenxuan Li, Alan Yuille, Zongwei Zhou
The pre-training and fine-tuning paradigm has become prominent in transfer learning. For example, if the model is pre-trained on ImageNet and then fine-tuned to PASCAL, it can sign…
RadGPT: Constructing 3D Image-Text Tumor Datasets
Pedro R. A. S. Bassi, Mehmet Can Yavuz, Kang Wang +7
Cancers identified in CT scans are usually accompanied by detailed radiology reports, but publicly available CT datasets often lack these essential reports. This absence limits the…