2 citations · 4 across the 9 of their papers we have counts for
7 papers · 1 filter
BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routine
Yang Liu, Jiajin Zhang, Danyang Tu +8
Breast cancer remains a leading cause of cancer-related mortality among women. Its clinical management requires multimodal reasoning across a clinical workflow that spans \textit{s…
Opportunistic Bone-Loss Screening from Routine Knee Radiographs Using a Multi-Task Deep Learning Framework with Sensitivity-Constrained Threshold Optimization
Zhaochen Li, Xinghao Yan, Runni Zhou +8
Background: Osteoporosis and osteopenia are often undiagnosed until fragility fractures occur. Dual-energy X-ray absorptiometry (DXA) is the reference standard for bone mineral den…
Non-Contrast CT Esophageal Varices Grading through Clinical Prior-Enhanced Multi-Organ Analysis
Xiaoming Zhang, Chunli Li, Jiacheng Hao +9
Esophageal varices (EV) represent a critical complication of portal hypertension, affecting approximately 60% of cirrhosis patients with a significant bleeding risk of ~30%. While…
LIDIA: Precise Liver Tumor Diagnosis on Multi-Phase Contrast-Enhanced CT via Iterative Fusion and Asymmetric Contrastive Learning
Wei Huang, Wei Liu, Xiaoming Zhang +9
The early detection and precise diagnosis of liver tumors are tasks of critical clinical value, yet they pose significant challenges due to the high heterogeneity and variability o…
Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration
Tony C. W. Mok, Zi Li, Yunhao Bai +9
Establishing dense anatomical correspondence across distinct imaging modalities is a foundational yet challenging procedure for numerous medical image analysis studies and image-gu…
SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation
Fan Bai, Ke Yan, Xiaoyu Bai +6
Medical image analysis using deep learning is often challenged by limited labeled data and high annotation costs. Fine-tuning the entire network in label-limited scenarios can lead…