article

Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images

Authors:

Habibollah Danyali,

Mohammad Sadegh HelfroushAuthors Info & Claims

Journal of Medical Systems, Volume 41, Issue 9

Pages 1 - 15

https://doi.org/10.1007/s10916-017-0773-9

Published: 01 September 2017 Publication History

Abstract

Based on the Nottingham criteria, the number of mitosis cells in histopathological slides is an important factor in diagnosis and grading of breast cancer. For manual grading of mitosis cells, histopathology slides of the tissue are examined by pathologists at 40 magnification for each patient. This task is very difficult and time-consuming even for experts. In this paper, a fully automated method is presented for accurate detection of mitosis cells in histopathology slide images. First a method based on maximum-likelihood is employed for segmentation and extraction of mitosis cell. Then a novel Maximized Inter-class Weighted Mean (MIWM) method is proposed that aims at reducing the number of extracted non-mitosis candidates that results in reducing the false positive mitosis detection rate. Finally, segmented candidates are classified into mitosis and non-mitosis classes by using a support vector machine (SVM) classifier. Experimental results demonstrate a significant improvement in accuracy of mitosis cells detection in different grades of breast cancer histopathological images.

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Cited By

Piansaddhayanaon CSantisukwongchote SShuangshoti STao QSriswasdi SChuangsuwanich E(2023)ReCasNetArtificial Intelligence in Medicine10.1016/j.artmed.2022.102462135:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.artmed.2022.102462
Rashmi RPrasad KUdupa C(2022)Region-based feature enhancement using channel-wise attention for classification of breast histopathological imagesNeural Computing and Applications10.1007/s00521-022-07966-z35:8(5839-5854)Online publication date: 8-Nov-2022
https://dl.acm.org/doi/10.1007/s00521-022-07966-z

Maximized Inter-Class Weighted Mean for Fast and Accurate Mitosis Cells Detection in Breast Cancer Histopathology Images
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
    2. Machine learning algorithms

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Published In

cover image Journal of Medical Systems

Journal of Medical Systems Volume 41, Issue 9

September 2017

164 pages

ISSN:0148-5598

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Copyright © Copyright © 2017 Springer Science+Business Media, LLC.

Publisher

Plenum Press

United States

Publication History

Published: 01 September 2017

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Cited By

Piansaddhayanaon CSantisukwongchote SShuangshoti STao QSriswasdi SChuangsuwanich E(2023)ReCasNetArtificial Intelligence in Medicine10.1016/j.artmed.2022.102462135:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.artmed.2022.102462
Rashmi RPrasad KUdupa C(2022)Region-based feature enhancement using channel-wise attention for classification of breast histopathological imagesNeural Computing and Applications10.1007/s00521-022-07966-z35:8(5839-5854)Online publication date: 8-Nov-2022
https://dl.acm.org/doi/10.1007/s00521-022-07966-z

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