From the 1 of 37 linked papers with an AI index.
37 papers
Gaussian Meta-Space Augmentation for Stacking Ensembles in Multimodal IPMN Risk Stratification
Max A. Nelson, Eminenur Sen Tasci, Zhixiang Wang +12
Pancreatic cancer is among the most lethal malignancies; risk stratification of intraductal papillary mucinous neoplasms (IPMNs) offers a crucial opportunity for early intervention…
BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization
Hongyi Pan, Gorkem Durak, Halil Ertugrul Aktas +18
Breast density classification is a critical component of breast cancer risk assessment, yet AI models often struggle to generalize across clinical sites due to vendor-specific acqu…
Beyond Medical Diagnostics: How Medical Multimodal Large Language Models Think in Space
Quoc-Huy Trinh, Xi Ding, Yang Liu +7
The paper introduces SpatialMed, a benchmark and an automated pipeline that generates 3D spatial visual question‑answer pairs for medical imaging, and shows that current multimodal…
CORA: Generalizable coronary artery disease assessment and risk stratification from coronary CT angiography using pathology-centric representation learning
Jinkui Hao, Gorkem Durak, Halil Ertugrul Aktas +4
Coronary artery disease, a leading cause of cardiovascular mortality worldwide, can be assessed non-invasively by coronary computed tomography angiography (CCTA). Although deep lea…
SRMA-Mamba: Spatial Reverse Mamba Attention Network for Pathological Liver Segmentation in MRI Volumes
Jun Zeng, Quoc-Huy Trinh, Deepak Ranjan Nayak +3
Liver cirrhosis plays a critical role in the prognosis of chronic liver disease. Early detection and timely intervention are essential for reducing mortality rates. However, the in…
Revisiting LLM Adaptation for 3D CT Report Generation: A Study of Scaling and Diagnostic Priors
Vanshali Sharma, Andrea M. Bejar, Halil Ertugrul Aktas +4
Recent advances in multimodal learning, including large language models (LLMs) and vision-language models (VLMs), have demonstrated strong adaptability to natural images. However,…