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Research Article | Open Access |

Detection of Soft Atherosclerotic Plaques in Cardiac Computed Tomography Angiography

Author 1: Muhammad Moazzam Jawaid Author 2: Sajjad Ali Memon Author 3: Imran Ali Qureshi Author 4: Nasrullah Pirzada
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 9, No. 4 · Published 2018

DOI: https://doi.org/10.14569/IJACSA.2018.090406

Abstract

Computed tomography angiography (CTA) has turned non-invasive diagnosis of cardiovascular anomalies into a reality as state-of-the-art imaging equipment is capable of recording sub-millimeter details. Based on high intensity, the calcified plaques are easily identified in cardiac CTA; however, low density based non-calcified plaque detection has been a challenging problem in recent years. We propose an efficient method in this work for automated detection of the non-calcified plaques using discrete radial profiles. The plaque detection is accomplished using support vector machine to differentiate abnormal coronary segments. We investigated a total of 32 CTA volumes and the detection mean accuracy of 84.6% was achieved, which is in-line with the reported literature.

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How to Cite this Article

Jawaid, M. M., Memon, S. A., Qureshi, I. A., & Pirzada, N. (2018). Detection of Soft Atherosclerotic Plaques in Cardiac Computed Tomography Angiography. International Journal of Advanced Computer Science and Applications, 9(4). https://doi.org/10.14569/IJACSA.2018.090406

Jawaid, Muhammad Moazzam, et al.. "Detection of Soft Atherosclerotic Plaques in Cardiac Computed Tomography Angiography." International Journal of Advanced Computer Science and Applications, vol. 9, no. 4, 2018, https://doi.org/10.14569/IJACSA.2018.090406.

@article{Jawaid2018,
  title     = {Detection of Soft Atherosclerotic Plaques in Cardiac Computed Tomography Angiography},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {9},
  number    = {4},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Muhammad Moazzam Jawaid and Sajjad Ali Memon and Imran Ali Qureshi and Nasrullah Pirzada},
  doi       = {10.14569/IJACSA.2018.090406},
  url       = {https://doi.org/10.14569/IJACSA.2018.090406}
}

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