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Segmentation of Lumen and External Elastic Laminae in Intravascular Ultrasound Images Using Ultrasonic Backscattering Physics Initialized Multiscale Random Walks

  • Debarghya China
  • Pabitra Mitra
  • Debdoot SheetEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10481)

Abstract

Coronary artery disease accounts for a large number of deaths across the world and clinicians generally prefer using x-ray computed tomography or magnetic resonance imaging for localizing vascular pathologies. Interventional imaging modalities like intravascular ultrasound (IVUS) are used to adjunct diagnosis of atherosclerotic plaques in vessels, and help assess morphological state of the vessel and plaque, which play a significant role for treatment planning. Since speckle intensity in IVUS images are inherently stochastic in nature and challenge clinicians with accurate visibility of the vessel wall boundaries, it requires automation. In this paper we present a method for segmenting the lumen and external elastic laminae of the artery wall in IVUS images using random walks over a multiscale pyramid of Gaussian decomposed frames. The seeds for the random walker are initialized by supervised learning of ultrasonic backscattering and attenuation statistical mechanics from labelled training samples. We have experimentally evaluated the performance using 77 IVUS images acquired at 40 MHz that are available in the IVUS segmentation challenge dataset (http://www.cvc.uab.es/IVUSchallenge2011/dataset.html.) to obtain a Jaccard score of \(0.89 \pm 0.14\) for lumen and \(0.85 \pm 0.12\) for external elastic laminae segmentation over a 10-fold cross-validation study.

Keywords

External elastic laminae segmentation Intravascular ultrasound Lumen segmentation Random forests Random walks Signal confidence 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Advanced Technology Development CentreIndian Institute of Technology KharagpurKharagpurIndia
  2. 2.Department of Computer Science and EngineeringIndian Institute of Technology KharagpurKharagpurIndia
  3. 3.Department of Electrical EngineeringIndian Institute of Technology KharagpurKharagpurIndia

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