11 citations · 19 across the 5 of their papers we have counts for
6 papers
SupWMA: Consistent and Efficient Tractography Parcellation of Superficial White Matter with Deep Learning
Tengfei Xue, Fan Zhang, Chaoyi Zhang +6
White matter parcellation classifies tractography streamlines into clusters or anatomically meaningful tracts to enable quantification and visualization. Most parcellation methods…
Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation
Yuqian Chen, Chaoyi Zhang, Yang Song +5
White matter fiber clustering (WMFC) enables parcellation of white matter tractography for applications such as disease classification and anatomical tract segmentation. However, t…
Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: a review
Fan Zhang, Alessandro Daducci, Yong He +6
Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo mapping of the brain's white matter connections at macro scale. Over…
CellTrack R-CNN: A Novel End-To-End Deep Neural Network for Cell Segmentation and Tracking in Microscopy Images
Yuqian Chen, Yang Song, Chaoyi Zhang +4
Cell segmentation and tracking in microscopy images are of great significance to new discoveries in biology and medicine. In this study, we propose a novel approach to combine cell…
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-weighting
Dongnan Liu, Donghao Zhang, Yang Song +5
Unsupervised domain adaptation (UDA) for nuclei instance segmentation is important for digital pathology, as it alleviates the burden of labor-intensive annotation and domain shift…
TRAKO: Efficient Transmission of Tractography Data for Visualization
Daniel Haehn, Loraine Franke, Fan Zhang +4
Fiber tracking produces large tractography datasets that are tens of gigabytes in size consisting of millions of streamlines. Such vast amounts of data require formats that allow f…