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Border to Border Distance Based Method for Detecting Juxta-Pleural Nodules

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Computer Vision and Image Processing (CVIP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1376))

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Abstract

Accurate detection and segmentation of lung structures play a vital role in computer based lung cancer detection and diagnosis. Lung segmentation is challenging when the nodules are attached to the pleural walls of the lung boundary. This paper presents a novel methodology on detecting the lung structures to include the juxta-pleural nodules by calculating the shortest distance between two borders of the two consecutive slices. The proposed methodology is tested with some sample CT slices on Lung Image Database Consortium and Image Database Resource Initiative dataset. This work validates and demonstrates that the sequence based image processing is useful for detecting the nodules attached to the lung boundaries, juxta-pleural nodules.

This work was carried out at ABV- IIITM Gwalior, India with funding from DST, Govt. of India.

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Author information

Authors and Affiliations

  1. Atal Bihari Vajpayee Indian Institute of Information Technology and Management, Gwalior, Madhya Pradesh, India

    R. Jenkin Suji, W. Wilfred Godfrey & Joydip Dhar

Authors
  1. R. Jenkin Suji
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  2. W. Wilfred Godfrey
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  3. Joydip Dhar
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Corresponding author

Correspondence to R. Jenkin Suji .

Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology Allahabad, Prayagraj, India

    Satish Kumar Singh

  2. Indian Institute of Technology Roorkee, Roorkee, India

    Partha Roy

  3. Indian Institute of Technology Roorkee, Roorkee, India

    Balasubramanian Raman

  4. Indian Institute of Information Technology Allahabad, Prayagraj, India

    P. Nagabhushan

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Jenkin Suji, R., Wilfred Godfrey, W., Dhar, J. (2021). Border to Border Distance Based Method for Detecting Juxta-Pleural Nodules. In: Singh, S.K., Roy, P., Raman, B., Nagabhushan, P. (eds) Computer Vision and Image Processing. CVIP 2020. Communications in Computer and Information Science, vol 1376. Springer, Singapore. https://doi.org/10.1007/978-981-16-1086-8_22

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  • DOI: https://doi.org/10.1007/978-981-16-1086-8_22

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-1085-1

  • Online ISBN: 978-981-16-1086-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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