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Jawaid MM, Riaz A, Rajani R, et al. Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles. Comput Biol Med. 2017;89:84-95doi: 10.1016/j.compbiomed.2017.07.021.
Jawaid, M. M., Riaz, A., Rajani, R., Reyes-Aldasoro, C. C., & Slabaugh, G. (2017). Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles. Computers in biology and medicine, 8984-95. https://doi.org/10.1016/j.compbiomed.2017.07.021
Jawaid, Muhammad Moazzam, et al. "Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles." Computers in biology and medicine vol. 89 (2017): 84-95. doi: https://doi.org/10.1016/j.compbiomed.2017.07.021
Jawaid MM, Riaz A, Rajani R, Reyes-Aldasoro CC, Slabaugh G. Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles. Comput Biol Med. 2017 Oct 01;89:84-95. doi: 10.1016/j.compbiomed.2017.07.021. Epub 2017 Aug 01. PMID: 28797740.
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Comput Biol Med. 2017 Oct 01;89:84-95. doi: 10.1016/j.compbiomed.2017.07.021. Epub 2017 Aug 01.

Framework for detection and localization of coronary non-calcified plaques in cardiac CTA using mean radial profiles.

Computers in biology and medicine

Muhammad Moazzam Jawaid, Atif Riaz, Ronak Rajani, Constantino Carlos Reyes-Aldasoro, Greg Slabaugh

Affiliations

  1. City University of London, Northampton Square, London EC1V 0HB, UK; Mehran University of Engineering & Technology, Jamshoro, Pakistan. Electronic address: [email protected].
  2. City University of London, Northampton Square, London EC1V 0HB, UK.
  3. St Thomas' Hospital, Westminster Bridge Road, London SE1 7EH, UK.

PMID: 28797740 DOI: 10.1016/j.compbiomed.2017.07.021

Abstract

BACKGROUND AND OBJECTIVE: The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis of cardiovascular anomalies into reality as calcified coronary plaques can be easily identified due to their high intensity values. However, the detection of non-calcified plaques in CTA is still a challenging problem because of lower intensity values, which are often similar to the nearby blood and muscle tissues. In this work, we propose the use of mean radial profiles for the detection of non-calcified plaques in CTA imagery.

METHODS: Accordingly, we computed radial profiles by averaging the image intensity in concentric rings around the vessel centreline in a first stage. In the subsequent stage, an SVM classifier is applied to identify the abnormal coronary segments. For occluded segments, we further propose a derivative-based method to localize the position and length of the plaque inside the segment.

RESULTS: A total of 32 CTA volumes were analysed and a detection accuracy of 88.4% with respect to the manual expert was achieved. The plaque localization accuracy was computed using the Dice similarity coefficient and a mean of 83.2% was achieved.

CONCLUSION: The consistent performance for multi-vendor, multi-institution data demonstrates the reproducibility of our method across different CTA datasets with a good agreement with manual expert annotations.

Copyright © 2017 Elsevier Ltd. All rights reserved.

Keywords: Coronary segmentation; Non-calcified plaques; Plaque localization; Support vector machines

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