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Histopathological image classification using enhanced bag-of-feature with spiral biogeography-based optimization

  • Raju PalEmail author
  • Mukesh Saraswat
Article
  • 22 Downloads

Abstract

An exponential growth of histopathological digital images over the Internet requires an efficient method for organizing them properly for better retrieval and analysis process. For the same, an automatic histopathological image classification system can be useful. Moreover, such classification system may also be used to identify the inflamed and healthy tissues from tissue image datasets. However, complex background structures and heterogeneity among histopathological tissue images make it a complicated process. Therefore, this paper introduces an innovative method for categorization of histopathological images using an enhanced bag-of-feature framework. To obtain the optimal visual words in bag-of-features, a new spiral biogeography-based optimization algorithm has been proposed which introduces a spiral search and random search in the mutation operator to generate the suitability index variables. The efficacy of the spiral biogeography-based optimization algorithm has been tested on CEC 2017 benchmarks problems. Moreover, the applicability of the proposed classification method has been observed on two histopathological image datasets, Blue Histology image dataset and ADL Histopathological image dataset. The efficacy of the spiral biogeography-based optimization algorithm based bag-of-features method has been analyzed and compared with other state-of-the-art methods with respect to average accuracy, recall, precision, and F1-measure parameters.

Keywords

Histopathological image classification Bag-of-features Biogeography-based optimization 

Notes

Acknowledgements

Authors are thankful to Science and Engineering Research Board, Department of Science & Technology, Government of India, New Delhi, India for funding this work as part of the project (ECR/2016/000844).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Jaypee Institute of Information TechnologyNoidaIndia

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