Active Tuberculosis Detection On CXR Package for Bob¶
Package to train convolutional neural networks for tuberculosis detection on frontal chest X-rays. Additionally, this package implements prediction of TB on chest X-rays and evaluation of performances. It is build using PyTorch.
Please use the BibTeX reference below to cite this work:
@INPROCEEDINGS{raposo_union_2022,
author = {Raposo, Geoffrey and Trajman, Anete and Anjos, Andr{\'{e}}},
month = 11,
title = {Pulmonary Tuberculosis Screening from Radiological Signs on Chest X-Ray Images Using Deep Models},
booktitle = {Union World Conference on Lung Health},
year = {2022},
date = {2022-11-01},
organization = {The Union},
}
@TECHREPORT{Raposo_Idiap-Com-01-2021,
author = {Raposo, Geoffrey},
keywords = {deep learning, generalization, Interpretability, transfer learning, Tuberculosis Detection},
projects = {Idiap},
month = {7},
title = {Active tuberculosis detection from frontal chest X-ray images},
type = {Idiap-Com},
number = {Idiap-Com-01-2021},
year = {2021},
institution = {Idiap},
url = {https://gitlab.idiap.ch/bob/bob.med.tb},
pdf = {https://publidiap.idiap.ch/downloads/reports/2021/Raposo_Idiap-Com-01-2021.pdf}
}