PodNet: Ensemble-based Classification of Podocytopathy on Kidney Glomerular Images

George Oliveira Barros, George Oliveira Barros, David Campos Wanderley, Luciano Oliveira Rebouças, Washington L. C. dos Santos, Angelo A. Duarte, Flavio de Barros Vidal

2022

Abstract

Podocyte lesions in renal glomeruli are identified by pathologists using visual analyses of kidney tissue sections (histological images). By applying automatic visual diagnosis systems, one may reduce the subjectivity of analyses, accelerate the diagnosis process, and improve medical decision accuracy. Towards this direction, we present here a new data set of renal glomeruli histological images for podocitopathy classification and a deep neural network model. The data set consists of 835 digital images (374 with podocytopathy and 430 without podocytopathy), annotated by a group of pathologists. Our proposed method (called here PodNet) is a classification method based on deep neural networks (pre-trained VGG19) used as features extractor from images in different color spaces. We compared PodNet with other six state-of-the-art models in two data set versions (RGB and gray level) and two different training contexts: pre-trained models (transfer learning from Imagenet) and from-scratch, both with hyperparameters tuning. The proposed method achieved classification results to 90.9% of f1-score, 88.9% precision, and 93.2% of recall in the final validation sets.

Paper Citation

in Harvard Style

Barros G., Wanderley D., Rebouças L., Santos W., Duarte A. and Vidal F. (2022). PodNet: Ensemble-based Classification of Podocytopathy on Kidney Glomerular Images. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 405-412. DOI: 10.5220/0010828600003124

in Bibtex Style

@conference{visapp22,
author={George Oliveira Barros and David Campos Wanderley and Luciano Oliveira Rebouças and Washington L. C. dos Santos and Angelo A. Duarte and Flavio de Barros Vidal},
title={PodNet: Ensemble-based Classification of Podocytopathy on Kidney Glomerular Images},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP},
year={2022},
pages={405-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010828600003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP
TI - PodNet: Ensemble-based Classification of Podocytopathy on Kidney Glomerular Images
SN - 978-989-758-555-5
AU - Barros G.
AU - Wanderley D.
AU - Rebouças L.
AU - Santos W.
AU - Duarte A.
AU - Vidal F.
PY - 2022
SP - 405
EP - 412
DO - 10.5220/0010828600003124
PB - SciTePress