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Public Datasets and Techniques for Segmentation of Anatomical Structures from Chest X-Rays: Comparitive Study, Current Trends and Future Directions

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1036))

Abstract

Segmentation of anatomical structures from chest x ray has an increasing importance in the past four decades and researchers have proposed various techniques and evaluated them using different datasets. In order to evaluate and compare a proposed technique, it is necessary to have knowledge about public datasets available. In this survey, properties and characteristics of different public chest x ray datasets available for segmentation of anatomical structures are studied. Different approaches for segmentation of anatomical structures (lung, heart, clavicles) are summarized. Segmentation techniques for each anatomical structure for a given dataset are compared and analyzed. The paper outlines the issues where further research can be focused.

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Authors and Affiliations

  1. Vignan’s Foundation for Science Technology and Research, Guntur, Andhra Pradesh, India

    Ebenezer Jangam

  2. IIT (ISM) Dhanbad, Dhanbad, Jharkhand, India

    A. C. S. Rao

Authors
  1. Ebenezer Jangam
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  2. A. C. S. Rao
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Correspondence to Ebenezer Jangam .

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Editors and Affiliations

  1. Department of Computer Science, University of South Dakota, Vermillion, SD, USA

    K. C. Santosh

  2. Solapur University, Solapur, India

    Ravindra S. Hegadi

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Jangam, E., Rao, A.C.S. (2019). Public Datasets and Techniques for Segmentation of Anatomical Structures from Chest X-Rays: Comparitive Study, Current Trends and Future Directions. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1036. Springer, Singapore. https://doi.org/10.1007/978-981-13-9184-2_29

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  • DOI: https://doi.org/10.1007/978-981-13-9184-2_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9183-5

  • Online ISBN: 978-981-13-9184-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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