David Gage Ellis
Orcid: 0000-0002-3718-6836
According to our database1,
David Gage Ellis authored at least 68 papers
between 2014 and 2026.
Collaborative distances:
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Bibliography
2026
BONBID-HIE 2023: Lesion Segmentation Challenge in BOston Neonatal Brain Injury Data for Hypoxic Ischemic Encephalopathy.
IEEE Trans. Medical Imaging, April, 2026
2025
2024
Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model.
J. Medical Syst., December, 2024
2023
Towards clinical applicability and computational efficiency in automatic cranial implant design: An overview of the AutoImplant 2021 cranial implant design challenge.
Medical Image Anal., August, 2023
CoRR, 2023
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
2021
IEEE Trans. Medical Imaging, 2021
Proceedings of the Towards the Automatization of Cranial Implant Design in Cranioplasty II, 2021
2020
Deep Learning Using Augmentation via Registration: 1st Place Solution to the AutoImplant 2020 Challenge.
Proceedings of the Towards the Automatization of Cranial Implant Design in Cranioplasty, 2020
Trialing U-Net Training Modifications for Segmenting Gliomas Using Open Source Deep Learning Framework.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020
2019
2018
2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.1.
Dataset, May, 2017
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.13.0.
Dataset, May, 2017
2016
Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in Python. 0.12.0-rc1.
Dataset, April, 2016
2014
A reusable BIST with software assisted repair technology for improved memory and IO debug, validation and test time.
Proceedings of the 2014 International Test Conference, 2014