@inproceedings{2358f2e72791476dab4255c6f8c5db09,
title = "Neural Registration and Segmentation of White Matter Tracts in Multi-modal Brain MRI",
abstract = "Pre-surgical mapping of white matter (WM) tracts requires specific neuroanatomical knowledge and a significant amount of time. Currently, pre-surgical tractography workflows rely on classical registration tools that prospectively align the multiple brain MRI modalities required for the task. Brain lesions and patient motion may challenge the robustness and accuracy of these tool, eventually requiring additional manual intervention. We present a novel neural workflow for 3-D registration and segmentation of WM tracts in multiple brain MRI sequences. The method is applied to pairs of T1-weighted (T1w) and directionally encoded color (DEC) maps. Validation is provided on two different datasets, the Human Connectome Project (HCP) dataset, and a real pre-surgical dataset. The proposed method outperforms the state-of-the-art TractSeg and AGYnet algorithms on both datasets, quantitatively and qualitatively, suggesting its applicability to automatic WM tract mapping in neuro-surgical MRI.",
keywords = "Brain MRI, Convolutional neural networks, Multi-modal segmentation, Neuro-surgical planning, Registration, Tractography",
author = "Noa Barzilay and Ilya Nelkenbaum and Eli Konen and Nahum Kiryati and Arnaldo Mayer",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 17th European Conference on Computer Vision, ECCV 2022 ; Conference date: 23-10-2022 Through 27-10-2022",
year = "2023",
doi = "10.1007/978-3-031-25066-8_12",
language = "الإنجليزيّة",
isbn = "9783031250651",
series = "Lecture Notes in Computer Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "252--267",
editor = "Leonid Karlinsky and Tomer Michaeli and Ko Nishino",
booktitle = "Computer Vision – ECCV 2022 Workshops, Proceedings",
address = "ألمانيا",
}