no code implementations • 9 Jan 2024 • Yuxiang Wei, Yuqian Chen, Tengfei Xue, Leo Zekelman, Nikos Makris, Yogesh Rathi, Weidong Cai, Fan Zhang, Lauren J. O' Donnell
We present an explainable multi-view network (EMV-Net) that can use different anatomical views to improve prediction performance.
no code implementations • 18 Jul 2023 • Tengfei Xue, Yuqian Chen, Chaoyi Zhang, Alexandra J. Golby, Nikos Makris, Yogesh Rathi, Weidong Cai, Fan Zhang, Lauren J. O'Donnell
TractCloud achieves efficient and consistent whole-brain white matter parcellation across the lifespan (from neonates to elderly subjects, including brain tumor patients) without the need for registration.
no code implementations • 8 Jul 2023 • Yuqian Chen, Leo R. Zekelman, Chaoyi Zhang, Tengfei Xue, Yang song, Nikos Makris, Yogesh Rathi, Alexandra J. Golby, Weidong Cai, Fan Zhang, Lauren J. O'Donnell
We evaluate the effectiveness of the proposed method by predicting individual performance on two neuropsychological assessments of language using a dataset of 20 association white matter fiber tracts from 806 subjects from the Human Connectome Project.
1 code implementation • 25 Mar 2023 • Hao Xu, Tengfei Xue, Dongnan Liu, Fan Zhang, Carl-Fredrik Westin, Ron Kikinis, Lauren J. O'Donnell, Weidong Cai
Our method is constructed by proposed registration-based peak augmentation (RPA) and uncertainty-based refining (URe) modules.
1 code implementation • 2 Mar 2023 • Nabil Vindas, Nicole Labra Avila, Fan Zhang, Tengfei Xue, Lauren J. O'Donnell, Jean-François Mangin
Superficial white matter (SWM) has been less studied than long-range connections despite being of interest to clinical research, andfew tractography parcellation methods have been adapted to SWM.
no code implementations • 5 Jan 2023 • Yuqian Chen, Fan Zhang, Leo R. Zekelman, Tengfei Xue, Chaoyi Zhang, Yang song, Nikos Makris, Yogesh Rathi, Weidong Cai, Lauren J. O'Donnell
This work shows the potential of incorporating anatomical information, especially known anatomical similarities between input features, to guide convolutions in neural networks.
no code implementations • 15 Nov 2022 • Sipei Li, Jianzhong He, Tengfei Xue, Guoqiang Xie, Shun Yao, Yuqian Chen, Erickson F. Torio, Yuanjing Feng, Dhiego CA Bastos, Yogesh Rathi, Nikos Makris, Ron Kikinis, Wenya Linda Bi, Alexandra J Golby, Lauren J O'Donnell, Fan Zhang
The retinogeniculate pathway (RGVP) is responsible for carrying visual information from the retina to the lateral geniculate nucleus.
no code implementations • 11 Nov 2022 • Yuxiang Wei, Tengfei Xue, Yogesh Rathi, Nikos Makris, Fan Zhang, Lauren J. O'Donnell
The brain's white matter (WM) undergoes developmental and degenerative processes during the human lifespan.
no code implementations • 13 Oct 2022 • Tengfei Xue, Fan Zhang, Leo R. Zekelman, Chaoyi Zhang, Yuqian Chen, Suheyla Cetin-Karayumak, Steve Pieper, William M. Wells, Yogesh Rathi, Nikos Makris, Weidong Cai, Lauren J. O'Donnell
We propose a novel deep regression method, namely TractoSCR, that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography.
1 code implementation • 18 Jul 2022 • Tengfei Xue, Fan Zhang, Chaoyi Zhang, Yuqian Chen, Yang song, Alexandra J. Golby, Nikos Makris, Yogesh Rathi, Weidong Cai, Lauren J. O'Donnell
We propose a novel two-stage deep-learning-based framework, Superficial White Matter Analysis (SupWMA), that performs an efficient and consistent parcellation of 198 SWM clusters from whole-brain tractography.
no code implementations • 6 Jul 2022 • Yuqian Chen, Fan Zhang, Chaoyi Zhang, Tengfei Xue, Leo R. Zekelman, Jianzhong He, Yang song, Nikos Makris, Yogesh Rathi, Alexandra J. Golby, Weidong Cai, Lauren J. O'Donnell
In this paper, we propose a deep-learning-based framework for neuropsychological score prediction using microstructure measurements estimated from diffusion magnetic resonance imaging (dMRI) tractography, focusing on predicting performance on a receptive vocabulary assessment task based on a critical fiber tract for language, the arcuate fasciculus (AF).
no code implementations • 5 Jul 2022 • Fan Zhang, Tengfei Xue, Weidong Cai, Yogesh Rathi, Carl-Fredrik Westin, Lauren J O'Donnell
Whole brain tractography (WBT) data contains over hundreds of thousands of individual fiber streamlines (estimated brain connections), and this data is usually parcellated to create compact representations for data analysis applications such as disease classification.
1 code implementation • 2 May 2022 • Yuqian Chen, Chaoyi Zhang, Tengfei Xue, Yang song, Nikos Makris, Yogesh Rathi, Weidong Cai, Fan Zhang, Lauren J. O'Donnell
In this work, we propose a novel deep learning framework for white matter fiber clustering, Deep Fiber Clustering (DFC), which solves the unsupervised clustering problem as a self-supervised learning task with a domain-specific pretext task to predict pairwise fiber distances.
1 code implementation • 29 Jan 2022 • Tengfei Xue, Fan Zhang, Chaoyi Zhang, Yuqian Chen, Yang song, Nikos Makris, Yogesh Rathi, Weidong Cai, Lauren J. O'Donnell
Most parcellation methods focus on the deep white matter (DWM), while fewer methods address the superficial white matter (SWM) due to its complexity.