25 citations · 65 across the 32 of their papers we have counts for
7 papers · 1 filter
Bonnet: Ultra-fast whole-body bone segmentation from CT scans
Hanjiang Zhu, Pedro Martelleto Rezende, Zhang Yang +5
This work proposes Bonnet, an ultra-fast sparse-volume pipeline for whole-body bone segmentation from CT scans. Accurate bone segmentation is important for surgical planning and an…
Fundus2Globe: Generative AI-Driven 3D Digital Twins for Personalized Myopia Management
Danli Shi, Bowen Liu, Zhen Tian +6
Myopia, projected to affect 50% population globally by 2050, is a leading cause of vision loss. Eyes with pathological myopia exhibit distinctive shape distributions, which are clo…
Fundus2Video: Cross-Modal Angiography Video Generation from Static Fundus Photography with Clinical Knowledge Guidance
Weiyi Zhang, Siyu Huang, Jiancheng Yang +5
Fundus Fluorescein Angiography (FFA) is a critical tool for assessing retinal vascular dynamics and aiding in the diagnosis of eye diseases. However, its invasive nature and less a…
LeFusion: Controllable Pathology Synthesis via Lesion-Focused Diffusion Models
Hantao Zhang, Yuhe Liu, Jiancheng Yang +4
Patient data from real-world clinical practice often suffers from data scarcity and long-tail imbalances, leading to biased outcomes or algorithmic unfairness. This study addresses…
Deep Rib Fracture Instance Segmentation and Classification from CT on the RibFrac Challenge
Jiancheng Yang, Rui Shi, Liang Jin +22
Rib fractures are a common and potentially severe injury that can be challenging and labor-intensive to detect in CT scans. While there have been efforts to address this field, the…
Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation
Minghui Zhang, Yangqian Wu, Hanxiao Zhang +33
Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach o…
Asymmetric 3D Context Fusion for Universal Lesion Detection
Jiancheng Yang, Yi He, Kaiming Kuang +3
Modeling 3D context is essential for high-performance 3D medical image analysis. Although 2D networks benefit from large-scale 2D supervised pretraining, it is weak in capturing 3D…