2 papers
cs.CV2026
USCNet: Transformer-Based Multimodal Fusion with Segmentation Guidance for Urolithiasis Classification
Changmiao Wang, Songqi Zhang, Yongquan Zhang +9
Kidney stone disease ranks among the most prevalent conditions in urology, and understanding the composition of these stones is essential for creating personalized treatment plans…
cs.CV2025
MedGEN-Bench: Contextually entangled benchmark for open-ended multimodal medical generation
Junjie Yang, Yuhao Yan, Gang Wu +8
As Vision-Language Models (VLMs) increasingly gain traction in medical applications, clinicians are progressively expecting AI systems not only to generate textual diagnoses but al…