2 citations · 5 across the 8 of their papers we have counts for
9 papers
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…
PLUS: Plug-and-Play Enhanced Liver Lesion Diagnosis Model on Non-Contrast CT Scans
Jiacheng Hao, Xiaoming Zhang, Wei Liu +8
Focal liver lesions (FLL) are common clinical findings during physical examination. Early diagnosis and intervention of liver malignancies are crucial to improving patient survival…
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…
Improved Esophageal Varices Assessment from Non-Contrast CT Scans
Chunli Li, Xiaoming Zhang, Yuan Gao +5
Esophageal varices (EV), a serious health concern resulting from portal hypertension, are traditionally diagnosed through invasive endoscopic procedures. Despite non-contrast compu…
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…
Liver Tumor Screening and Diagnosis in CT with Pixel-Lesion-Patient Network
Ke Yan, Xiaoli Yin, Yingda Xia +10
Liver tumor segmentation and classification are important tasks in computer aided diagnosis. We aim to address three problems: liver tumor screening and preliminary diagnosis in no…
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization
Mingze Yuan, Yingda Xia, Hexin Dong +13
Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically signi…
CancerUniT: Towards a Single Unified Model for Effective Detection, Segmentation, and Diagnosis of Eight Major Cancers Using a Large Collection of CT Scans
Jieneng Chen, Yingda Xia, Jiawen Yao +22
Human readers or radiologists routinely perform full-body multi-organ multi-disease detection and diagnosis in clinical practice, while most medical AI systems are built to focus o…