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Open-source pipeline for multi-class segmentation of the spinal cord with deep learning.
Magn Reson Imaging. 2019 Dec;64:21-27. doi: 10.1016/j.mri.2019.04.009. Epub 2019 Apr 17.
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Automatic multiclass intramedullary spinal cord tumor segmentation on MRI with deep learning.
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Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter.
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Fully automated grey and white matter spinal cord segmentation.
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Spinal cord grey matter segmentation challenge.
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Gray matter segmentation of the spinal cord with active contours in MR images.
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Enhanced U-Net for Infant Brain MRI Segmentation: A (2+1)D Convolutional Approach.
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Regional spinal cord volumes and pain profiles in AQP4-IgG + NMOSD and MOGAD.
Front Neurol. 2024 Jan 26;15:1308498. doi: 10.3389/fneur.2024.1308498. eCollection 2024.
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Attention-gated U-Net networks for simultaneous axial/sagittal planes segmentation of injured spinal cords.
J Appl Clin Med Phys. 2023 Oct;24(10):e14123. doi: 10.1002/acm2.14123. Epub 2023 Sep 21.
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Role of artificial intelligence in MS clinical practice.
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Current Applications of Machine Learning in Spine: From Clinical View.
Global Spine J. 2022 Oct;12(8):1827-1840. doi: 10.1177/21925682211035363. Epub 2021 Oct 10.
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Mapping the rest of the human connectome: Atlasing the spinal cord and peripheral nervous system.
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AI in MRI: A case for grassroots deep learning.
Magn Reson Imaging. 2019 Dec;64:1-3. doi: 10.1016/j.mri.2019.07.004. Epub 2019 Jul 5.

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Generalised Dice Overlap as a Deep Learning Loss Function for Highly Unbalanced Segmentations.
Deep Learn Med Image Anal Multimodal Learn Clin Decis Support (2017). 2017;2017:240-248. doi: 10.1007/978-3-319-67558-9_28. Epub 2017 Sep 9.
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Unsupervised domain adaptation for medical imaging segmentation with self-ensembling.
Neuroimage. 2019 Jul 1;194:1-11. doi: 10.1016/j.neuroimage.2019.03.026. Epub 2019 Mar 19.
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The spectrum of spinal cord lesions in a primate model of multiple sclerosis.
Mult Scler. 2020 Mar;26(3):284-293. doi: 10.1177/1352458518822408. Epub 2019 Feb 7.
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Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.
Neuroimage. 2019 Jan 1;184:901-915. doi: 10.1016/j.neuroimage.2018.09.081. Epub 2018 Oct 6.
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Spatiotemporal distribution of fibrinogen in marmoset and human inflammatory demyelination.
Brain. 2018 Jun 1;141(6):1637-1649. doi: 10.1093/brain/awy082.
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Spinal cord gray matter segmentation using deep dilated convolutions.
Sci Rep. 2018 Apr 13;8(1):5966. doi: 10.1038/s41598-018-24304-3.
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NiftyNet: a deep-learning platform for medical imaging.
Comput Methods Programs Biomed. 2018 May;158:113-122. doi: 10.1016/j.cmpb.2018.01.025. Epub 2018 Jan 31.
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A survey on deep learning in medical image analysis.
Med Image Anal. 2017 Dec;42:60-88. doi: 10.1016/j.media.2017.07.005. Epub 2017 Jul 26.
9
Spinal cord grey matter segmentation challenge.
Neuroimage. 2017 May 15;152:312-329. doi: 10.1016/j.neuroimage.2017.03.010. Epub 2017 Mar 7.
10
Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter.
Neuroimage. 2017 Apr 15;150:358-372. doi: 10.1016/j.neuroimage.2016.09.026. Epub 2016 Sep 20.

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