TY - JOUR
AU - 
AB - 1, 2 1, 2 1, 2 Charley Gros , Andreanne Lemay , Olivier Vincent , Lucas 1 1 1 Rouhier , Marie-Helene Bourget , Anthime Bucquet , Joseph Paul 2, 3 1, 2, 4 Cohen , and Julien Cohen-Adad 1 NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montreal, Montreal, Canada 2 Mila, Quebec AI Institute, Montreal, QC, Canada 3 AIMI, Stanford University, Stanford, CA, USA 4 Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montreal, QC, Canada DOI: 10.21105/joss.02868 Software • Review Summary • Repository • Archive ivadomedisanopen-sourcePythonpackagefordesigning, end-to-endtraining, andevaluating deep learning models applied to medical imaging data. The package includes APIs, command- line tools, documentation, and tutorials. ivadomed also includes pre-trained models such as Editor: Christopher R. Madan spinal tumor segmentation and vertebral labeling. Original features of ivadomed include a Reviewers: data loader that can parse image and subject metadata for custom data splitting or extra • @NMontanaBrown information during training and evaluation. Any dataset following the Brain Imaging Data • @justusschock Structure (BIDS) convention will be compatible with ivadomed. Beyond the traditional deep • @lbugnon learning methods, ivadomed features cutting-edge architectures, such as FiLM (Perez et al., 2017) and HeMis (Havaei et al., 2016), as well as various 
TI - ivadomed: A Medical Imaging Deep Learning Toolbox
JF - Journal of Open Source Software
DO - 10.21105/joss.02868
DA - 2021-02-12
UR - https://www.deepdyve.com/lp/unpaywall/ivadomed-a-medical-imaging-deep-learning-toolbox-ke1presY8x
DP - DeepDyve
ER -