Multi-task Library to Develop Computer-Aided Tools for Medical Data Analysis¶
Framework for development and analysis of deep neural network architectures applied to medical data (images, 2D and 3D). This package can be readily used on a number of public datasets. It can be extended to add more datasets, and models.
Use one or more the BibTeX references below to cite this work:
@misc{guler_2024,
title = {Refining {Tuberculosis} {Detection} in {CXR} {Imaging}: {Addressing} {Bias} in {Deep} {Neural} {Networks} via {Interpretability}},
url = {http://arxiv.org/abs/2407.14064},
publisher = {arXiv},
author = {Güler, Özgür Acar and Günther, Manuel and Anjos, André},
month = jul,
year = {2024},
note = {arXiv:2407.14064 [cs]},
annote = {Comment: Preprint of paper presented at EUVIP 2024},
}
@misc{laibacher_2019,
title = {On the Evaluation and Real-World Usage Scenarios of Deep Vessel Segmentation for Retinography},
author = {Tim Laibacher and Andr\'e Anjos},
year = {2019},
eprint = {1909.03856},
archivePrefix = {arXiv},
primaryClass = {cs.CV},
url = {https://arxiv.org/abs/1909.03856},
}