Classification of Histopathological Images using Scale-Invariant Feature Transform

Andrzej Bukała, Bogusław Cyganek, Bogusław Cyganek, Michał Koziarski, Michał Koziarski, Bogdan Kwolek, Bogdan Kwolek, Bogusław Olborski, Zbigniew Antosz, Jakub Swadźba, Jakub Swadźba, Piotr Sitkowski

2020

Abstract

Throughout the years, Scale-Invariant Feature Transform (SIFT) was a widely adopted method in the image matching and classification tasks. However, due to the recent advances in convolutional neural networks, the popularity of SIFT and other similar feature descriptors significantly decreased, leaving SIFT underresearched in some of the emerging applications. In this paper we examine the suitability of SIFT feature descriptors in one such task, the histopathological image classification. In the conducted experimental study we investigate the usefulness of various variants of SIFT on the BreakHis Breast Cancer Histopathological Database. While colour is known to be significant in case of human performed analysis of histopathological images, SIFT variants using different colour spaces have not been thoroughly examined on this type of data before. Observed results indicate the effectiveness of selected SIFT variants, particularly Hue-SIFT, which outperformed the reference convolutional neural network ensemble on some of the considered magnifications, simultaneously achieving lower variance. This proves the importance of using different colour spaces in classification tasks with histopathological data and shows promise to find its use in diversifying classifier ensembles.

Paper Citation

in Harvard Style

Bukała A., Cyganek B., Koziarski M., Kwolek B., Olborski B., Antosz Z., Swadźba J. and Sitkowski P. (2020). Classification of Histopathological Images using Scale-Invariant Feature Transform. In Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP; ISBN 978-989-758-402-2, SciTePress, pages 506-512. DOI: 10.5220/0009163405060512

in Bibtex Style

@conference{visapp20,
author={Andrzej Bukała and Bogusław Cyganek and Michał Koziarski and Bogdan Kwolek and Bogusław Olborski and Zbigniew Antosz and Jakub Swadźba and Piotr Sitkowski},
title={Classification of Histopathological Images using Scale-Invariant Feature Transform},
booktitle={Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP},
year={2020},
pages={506-512},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009163405060512},
isbn={978-989-758-402-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020) - Volume 5: VISAPP
TI - Classification of Histopathological Images using Scale-Invariant Feature Transform
SN - 978-989-758-402-2
AU - Bukała A.
AU - Cyganek B.
AU - Koziarski M.
AU - Kwolek B.
AU - Olborski B.
AU - Antosz Z.
AU - Swadźba J.
AU - Sitkowski P.
PY - 2020
SP - 506
EP - 512
DO - 10.5220/0009163405060512
PB - SciTePress