Improved CTA coronary segmentation with a volume-specific intensity threshold

Muhammad Moazzam Jawaid, Ronak Rajani, Panos Liatsis, Constantino Carlos Reyes-Aldasoro, Greg Slabaugh

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

State-of-the-art CTA imaging equipment has increased clinician’s ability to make non-invasive diagnoses of coronary heart disease; however, an effective interpretation of the cardiac CTA becomes cumbersome due to large amount of imaged data. Intensity based background suppression is often used to enhance the coronary vasculature but setting a fixed threshold to discriminate coronaries from fatty muscles could be misleading due to non-homogeneous response of contrast medium in CTA volumes. In this work, we propose a volume-specific model of the contrast medium in the coronary segmentation process to improve the segmentation accuracy. The influence of the contrast medium in a CTA volume was modelled by approximating the intensity histogram of the descending aorta with Gaussian approximation. It should be noted that a significant variation in Gaussian mean for 12 CTA volumes validates the need of volume-wise exclusive intensity threshold for accurate coronary segmentation. Moreover, the effectiveness of the adaptive intensity threshold is illustrated with the help of qualitative and quantitative results.

Original languageBritish English
Title of host publicationMedical Image Understanding and Analysis - 21st Annual Conference, MIUA 2017, Proceedings
EditorsVictor Gonzalez-Castro, Maria Valdes Hernandez
PublisherSpringer Verlag
Pages207-218
Number of pages12
ISBN (Print)9783319609638
DOIs
StatePublished - 2017
Event21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017 - Edinburgh, United Kingdom
Duration: 11 Jul 201713 Jul 2017

Publication series

NameCommunications in Computer and Information Science
Volume723
ISSN (Print)1865-0929

Conference

Conference21st Annual Conference on Medical Image Understanding and Analysis, MIUA 2017
Country/TerritoryUnited Kingdom
CityEdinburgh
Period11/07/1713/07/17

Keywords

  • Computed tomography angiography
  • Contrast medium
  • Coronary segmentation
  • Curve evolution

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