activity
20242026
collaborators

7 papers

cs.CV2026

Early and Prediagnostic Detection of Pancreatic Cancer from Computed Tomography

Wenxuan Li, Pedro R. A. S. Bassi, Lizhou Wu +34

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest solid malignancies, is often detected at a late and inoperable stage. Retrospective reviews of prediagnostic CT scans,…

cs.CV2025

Scaling Artificial Intelligence for Multi-Tumor Early Detection with More Reports, Fewer Masks

Pedro R. A. S. Bassi, Xinze Zhou, Wenxuan Li +20

Early tumor detection save lives. Each year, more than 300 million computed tomography (CT) scans are performed worldwide, offering a vast opportunity for effective cancer screenin…

cs.CV2025

Training with Explanations Alone: A New Paradigm to Prevent Shortcut Learning

Pedro R. A. S. Bassi, Haydr A. H. Ali, Andrea Cavalli +1

Application of Artificial Intelligence (AI) in critical domains, like the medical one, is often hampered by shortcut learning, which hinders AI generalization to diverse hospitals…

eess.IV2025

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…

eess.IV2025

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…

cs.CV2025

Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?

Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50

How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…