136 citations · 295 across the 20 of their papers we have counts for
8 papers · 1 filter
VesselMorph: Domain-Generalized Retinal Vessel Segmentation via Shape-Aware Representation
Dewei Hu, Hao Li, Han Liu +3
Due to the absence of a single standardized imaging protocol, domain shift between data acquired from different sites is an inherent property of medical images and has become a maj…
CATS v2: Hybrid encoders for robust medical segmentation
Hao Li, Han Liu, Dewei Hu +3
Convolutional Neural Networks (CNNs) have exhibited strong performance in medical image segmentation tasks by capturing high-level (local) information, such as edges and textures.…
Democratizing Pathological Image Segmentation with Lay Annotators via Molecular-empowered Learning
Ruining Deng, Yanwei Li, Peize Li +11
Multi-class cell segmentation in high-resolution Giga-pixel whole slide images (WSI) is critical for various clinical applications. Training such an AI model typically requires lab…
Deep Angiogram: Trivializing Retinal Vessel Segmentation
Dewei Hu, Xing Yao, Jiacheng Wang +2
Among the research efforts to segment the retinal vasculature from fundus images, deep learning models consistently achieve superior performance. However, this data-driven approach…
Why is the winner the best?
Matthias Eisenmann, Annika Reinke, Vivienn Weru +122
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…
Self-Supervised CSF Inpainting with Synthetic Atrophy for Improved Accuracy Validation of Cortical Surface Analyses
Jiacheng Wang, Kathleen E. Larson, Ipek Oguz
Accuracy validation of cortical thickness measurement is a difficult problem due to the lack of ground truth data. To address this need, many methods have been developed to synthet…
SSL^2: Self-Supervised Learning meets Semi-Supervised Learning: Multiple Sclerosis Segmentation in 7T-MRI from large-scale 3T-MRI
Jiacheng Wang, Hao Li, Han Liu +6
Automated segmentation of multiple sclerosis (MS) lesions from MRI scans is important to quantify disease progression. In recent years, convolutional neural networks (CNNs) have sh…
Indescribable Multi-modal Spatial Evaluator
Lingke Kong, X. Sharon Qi, Qijin Shen +4
Multi-modal image registration spatially aligns two images with different distributions. One of its major challenges is that images acquired from different imaging machines have di…