ivadomed swMATH ID: 35828 Software Authors: Charley Gros, Andreanne Lemay, Olivier Vincent, Lucas Rouhier, Anthime Bucquet, Joseph Paul Cohen, Julien Cohen-Adad Description: ivadomed: A Medical Imaging Deep Learning Toolbox. ivadomed is an open-source Python package for designing, end-to-end training, and evaluating 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 spinal tumor segmentation and vertebral labeling. Original features of ivadomed include a data loader that can parse image metadata (e.g., acquisition parameters, image contrast, resolution) and subject metadata (e.g., pathology, age, sex) for custom data splitting or extra information during training and evaluation. Any dataset following the Brain Imaging Data Structure (BIDS) convention will be compatible with ivadomed without the need to manually organize the data, which is typically a tedious task. Beyond the traditional deep learning methods, ivadomed features cutting-edge architectures, such as FiLM and HeMis, as well as various uncertainty estimation methods (aleatoric and epistemic), and losses adapted to imbalanced classes and non-binary predictions. Each step is conveniently configurable via a single file. At the same time, the code is highly modular to allow addition/modification of an architecture or pre/post-processing steps. Example applications of ivadomed include MRI object detection, segmentation, and labeling of anatomical and pathological structures. Overall, ivadomed enables easy and quick exploration of the latest advances in deep learning for medical imaging applications. Homepage: https://ivadomed.org/en/latest/ Source Code: https://github.com/ivadomed/ivadomed Dependencies: Python Keywords: Image Processing; Video Processing; arXiv_eess.IV; Computer Vision; Pattern Recognition; arXiv_cs.CV; Python; Medical Imaging Related Software: Count-ception; V-Net; FiLM; QuickNAT; mixup; PyTorch; U-Net; SCT; Python Cited in: 0 Publications Standard Articles 1 Publication describing the Software Year ivadomed: A Medical Imaging Deep Learning Toolbox Charley Gros, Andreanne Lemay, Olivier Vincent, Lucas Rouhier, Anthime Bucquet, Joseph Paul Cohen, Julien Cohen-Adad 2020