14 citations · 18 across the 12 of their papers we have counts for
14 papers
Self-correction Optimization for Interleaved Multimodal Generation
Xin You, Zhiwei Ning, Zukai Chen +7
Multimodal large language models (MLLMs) have made significant progress in visual understanding and generation. However, generating interleaved image--text content remains challeng…
Towards Voxel Spacing Consistency for Medical Image Segmentation
Xin You, Runze Yang, Minghui Zhang +6
Volumetric medical image segmentation is essential for both preoperative diagnosis and intraoperative guidance. While recent years have witnessed rapid progress in segmentation arc…
TubeMLLM: A Foundation Model for Topology Knowledge Exploration in Vessel-like Anatomy
Yaoyu Liu, Minghui Zhang, Xin You +2
Modeling medical vessel-like anatomy is challenging due to its intricate topology and sensitivity to dataset shifts. Consequently, task-specific models often suffer from topologica…
TopoSculpt: Betti-Steered Topological Sculpting of 3D Fine-grained Tubular Shapes
Minghui Zhang, Yaoyu Liu, Junyang Wu +4
Medical tubular anatomical structures are inherently three-dimensional conduits with lumens, enclosing walls, and complex branching topologies. Accurate reconstruction of their geo…
Temporal Differential Fields for 4D Motion Modeling via Image-to-Video Synthesis
Xin You, Minghui Zhang, Hanxiao Zhang +2
Temporal modeling on regular respiration-induced motions is crucial to image-guided clinical applications. Existing methods cannot simulate temporal motions unless high-dose imagin…
Shape-aware Sampling Matters in the Modeling of Multi-Class Tubular Structures
Minghui Zhang, Yaoyu Liu, Xin You +2
Accurate multi-class tubular modeling is critical for precise lesion localization and optimal treatment planning. Deep learning methods enable automated shape modeling by prioritiz…
HASD: Hierarchical Adaption for pathology Slide-level Domain-shift
Jingsong Liu, Han Li, Chen Yang +6
Domain shift is a critical problem for pathology AI as pathology data is heavily influenced by center-specific conditions. Current pathology domain adaptation methods focus on imag…
Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge
Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60
Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…
Topology-Aware Exploration of Circle of Willis for CTA and MRA: Segmentation, Detection, and Classification
Minghui Zhang, Xin You, Hanxiao Zhang +1
The Circle of Willis (CoW) vessels is critical to connecting major circulations of the brain. The topology of the vascular structure is clinical significance to evaluate the risk,…
PASS:Test-Time Prompting to Adapt Styles and Semantic Shapes in Medical Image Segmentation
Chuyan Zhang, Hao Zheng, Xin You +2
Test-time adaptation (TTA) has emerged as a promising paradigm to handle the domain shifts at test time for medical images from different institutions without using extra training…
SLoRD: Structural Low-Rank Descriptors for Shape Consistency in Vertebrae Segmentation
Xin You, Yixin Lou, Minghui Zhang +2
Automatic and precise multi-class vertebrae segmentation from CT images is crucial for various clinical applications. However, due to similar appearances between adjacent vertebrae…
PnPNet: Pull-and-Push Networks for Volumetric Segmentation with Boundary Confusion
Xin You, Ming Ding, Minghui Zhang +4
Precise boundary segmentation of volumetric images is a critical task for image-guided diagnosis and computer-assisted intervention, especially for boundary confusion in clinical p…
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to influence the risk, severity, an…
Learning with Explicit Shape Priors for Medical Image Segmentation
Xin You, Junjun He, Jie Yang +1
Medical image segmentation is a fundamental task for medical image analysis and surgical planning. In recent years, UNet-based networks have prevailed in the field of medical image…