2 citations · 4 across the 10 of their papers we have counts for
10 papers
EliSeg: Verified Target Construction for Report-Grounded Abnormality Segmentation
Chengyi Peng, Haoyu Yang, Meixing Shi +2
Radiology reports describe clinical observations but do not specify executable segmentation targets. They may contain present, negated, prior,uncertain, or irrelevant findings, whi…
MedPixel: A Unified Pixel-Language Model for Medical Reasoning and Segmentation
Haoyu Yang, Meixing Shi, Zengjie Chen +5
Reliable medical image understanding requires models to connect clinical language and visual reasoning with pixel-level grounding. Yet medical vision-language models often lack pre…
IBISAgent: Reinforcing Pixel-Level Visual Reasoning in MLLMs for Universal Biomedical Object Referring and Segmentation
Yankai Jiang, Qiaoru Li, Binlu Xu +6
Recent research on medical MLLMs has gradually shifted its focus from image-level understanding to fine-grained, pixel-level comprehension. Although segmentation serves as the foun…
ROFI: A Deep Learning-Based Ophthalmic Sign-Preserving and Reversible Patient Face Anonymizer
Yuan Tian, Min Zhou, Yitong Chen +19
Patient face images provide a convenient mean for evaluating eye diseases, while also raising privacy concerns. Here, we introduce ROFI, a deep learning-based privacy protection fr…
Kernel-based Unsupervised Embedding Alignment for Enhanced Visual Representation in Vision-language Models
Shizhan Gong, Yankai Jiang, Qi Dou +1
Vision-language models, such as CLIP, have achieved significant success in aligning visual and textual representations, becoming essential components of many multi-modal large lang…
TK-Mamba: Marrying KAN With Mamba for Text-Driven 3D Medical Image Segmentation
Haoyu Yang, Yutong Guan, Meixing Shi +8
3D medical image segmentation is important for clinical diagnosis and treatment but faces challenges from high-dimensional data and complex spatial dependencies. Traditional single…
A Synthetic Data-Driven Radiology Foundation Model for Pan-tumor Clinical Diagnosis
Wenhui Lei, Hanyu Chen, Zitian Zhang +13
AI-assisted imaging made substantial advances in tumor diagnosis and management. However, a major barrier to developing robust oncology foundation models is the scarcity of large-s…
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
Yankai Jiang, Wenhui Lei, Xiaofan Zhang +1
Recent advancements in medical vision-language pre-training models have driven significant progress in zero-shot disease recognition. However, transferring image-level knowledge to…
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation
Zhongzhen Huang, Yankai Jiang, Rongzhao Zhang +2
Existing promptable segmentation methods in the medical imaging field primarily consider either textual or visual prompts to segment relevant objects, yet they often fall short whe…
ZePT: Zero-Shot Pan-Tumor Segmentation via Query-Disentangling and Self-Prompting
Yankai Jiang, Zhongzhen Huang, Rongzhao Zhang +2
The long-tailed distribution problem in medical image analysis reflects a high prevalence of common conditions and a low prevalence of rare ones, which poses a significant challeng…