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Automatic Localization of the Left Ventricle from Short-Axis MR Images Using Circular Hough Transform

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Proceedings of the Third International Conference on Trends in Computational and Cognitive Engineering

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 348))

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Abstract

The localization of the left ventricle (LV) automatically from cardiac magnetic resonance images (CMRI) is an important initial step during segmentation to quantify global and regional volumetric functions of LV such as volume, mass, and ejection fraction. The exact quantification of these indicators results in an accurate system for cardiac disease detection. Conventionally, LV localization in magnetic resonance (MR) images is implemented manually by experts, which is a tedious task and time-consuming. This paper proposes an automated localization method for LV from the cardiac short-axis MR images. The technique applies a circular Hough transform (CHT) to localize the LV with optimized performance. The results revealed that the accuracy of the proposed technique is 89.5% based on the range radius of the LV circle.

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Acknowledgements

This research was supported by the Ministry of Higher Education (MOHE) through Fundamental Research Grant Scheme (FRGS) (FRGS/1/2020/TK0/UTHM/02/16) and Universiti Tun Hussein Onn Malaysia (UTHM) through FRGS Research Grant (Vot K304).

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Authors and Affiliations

  1. Department of Electronic Engineering, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400, Parit Raja, Batu Pahat, Johor, Malaysia

    Zakarya Farea Shaaf, Muhammad Mahadi Abdul Jamil & Radzi Ambar

Authors
  1. Zakarya Farea Shaaf
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  2. Muhammad Mahadi Abdul Jamil
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  3. Radzi Ambar
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Corresponding author

Correspondence to Muhammad Mahadi Abdul Jamil .

Editor information

Editors and Affiliations

  1. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  2. Amity University Rajasthan, Jaipur, India

    Kanad Ray

  3. Surface Characterization Group, National Institute for Materials Science, Tsukuba, Japan

    Anirban Bandyopadhyay

  4. Faculty of Applied Sciences and Technology, Tun Hussein Onn University of Malaysia, Parit Raja, Johor, Malaysia

    Kavikumar Jacob

  5. Faculty of Applied Sciences and Technology (FAST), Universiti Tun Hussein Onn Malaysia, Johor, Malaysia

    Kek Sie Long

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Shaaf, Z.F., Jamil, M.M.A., Ambar, R. (2022). Automatic Localization of the Left Ventricle from Short-Axis MR Images Using Circular Hough Transform. In: Kaiser, M.S., Ray, K., Bandyopadhyay, A., Jacob, K., Long, K.S. (eds) Proceedings of the Third International Conference on Trends in Computational and Cognitive Engineering. Lecture Notes in Networks and Systems, vol 348. Springer, Singapore. https://doi.org/10.1007/978-981-16-7597-3_41

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