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Multi-Scale Directional Mask Pattern for Medical Image Classification and Retrieval

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Proceedings of 2nd International Conference on Computer Vision & Image Processing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 703))

Abstract

This paper presents a classification scheme for interstitial lung disease (ILD) pattern using patch-based approach and artificial neural network (ANN) classifier. A new feature descriptor, Multi-Scale Directional Mask Pattern (MSDMP), is proposed for feature extraction. Proposed MSDMP extracts microstructure information from a (31 × 31) size patches of the region of interest (ROI) which were marked by the radiologists. A two-layer feed-forward neural network is used for classification of ILD patterns. Also, proposed MSDMP feature descriptor has been tested on medical image retrieval system to check its robustness. Two benchmark medical datasets are used to evaluate the proposed descriptor. Performance analysis shows that the proposed feature descriptor outperforms the other existing state-of-the-art methods in terms of average recognition rate (ARR) and F-score.

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Authors and Affiliations

  1. Department of Electronics & Telecommunication Engineering, SGGSIE&T, Nanded, India

    Akshay A. Dudhane & Sanjay N. Talbar

Authors
  1. Akshay A. Dudhane
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  2. Sanjay N. Talbar
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Correspondence to Akshay A. Dudhane .

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Editors and Affiliations

  1. Computer Vision and Pattern Recognition Unit, Indian Statistical Institute, Kolkata, India

    Bidyut B. Chaudhuri

  2. School of Computing, National University of Singapore, Singapore, Singapore

    Mohan S. Kankanhalli

  3. Department of Computer Science and Engineering, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Balasubramanian Raman

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Dudhane, A.A., Talbar, S.N. (2018). Multi-Scale Directional Mask Pattern for Medical Image Classification and Retrieval. In: Chaudhuri, B., Kankanhalli, M., Raman, B. (eds) Proceedings of 2nd International Conference on Computer Vision & Image Processing . Advances in Intelligent Systems and Computing, vol 703. Springer, Singapore. https://doi.org/10.1007/978-981-10-7895-8_27

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  • DOI: https://doi.org/10.1007/978-981-10-7895-8_27

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7894-1

  • Online ISBN: 978-981-10-7895-8

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