Modified wavelet transform features for characterizing different plaque types in IVUS images; A feasibility study

Roodaki, Alireza; Taki, Arash; Setarehdan, Seyed Kamaledin; Navab, Nassir

doi:10.1109/icosp.2008.4697248

Cited by 6 publications

(2 citation statements)

References 10 publications

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“…Although there are methods that work with the B-mode image [5,6], the most successful approaches are those focused on the characterization of atherosclerotic plaque composition by analysis of the ultrasound RF signal. Nair et al [7] proposed a method known as "virtual histology" (IVUS-VH).…”

Section: Limitationsmentioning

confidence: 99%

An Inverse Scattering Algorithm for the Segmentation of the Luminal Border on Intravascular Ultrasound Data

Mendizabal-Ruiz

Biros

Kakadiaris

2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

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Abstract. Intravascular ultrasound (IVUS) is a catheter-based medical imaging technique that produces cross-sectional images of blood vessels and is particularly useful for studying atherosclerosis. In this paper, we present a novel method for segmentation of the luminal border on IVUS images using the radio frequency (RF) raw signal based on a scattering model and an inversion scheme. The scattering model is based on a random distribution of point scatterers in the vessel. The per-scatterer signal uses a differential backscatter cross-section coefficient (DBC) that depends on the tissue type. Segmentation requires two inversions: a calibration inversion and a reconstruction inversion. In the calibration step, we use a single manually segmented frame and then solve an inverse problem to recover the DBC for the lumen and vessel wall (κ l and κ w , respectively) and the width of the impulse signal σ. In the reconstruction step, we use the parameters from the calibration step to solve a new inverse problem: for each angle Θi of the IVUS data, we reconstruct the lumen-vessel wall interface. We evaluated our method using three 40MHz IVUS sequences by comparing with manual segmentations. Our preliminary results indicate that it is possible to segment the luminal border by solving an inverse problem using the IVUS RF raw signal with the scatterer model.

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Section: Limitationsmentioning

confidence: 99%

An Inverse Scattering Algorithm for the Segmentation of the Luminal Border on Intravascular Ultrasound Data

Mendizabal-Ruiz

Biros

Kakadiaris

2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

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“…Kawasaki et al [5] proposed a tissue classification method using features computed with from integrated backscatter of the RF signal. The feasibility of using wavelet analysis for plaque characterization using the RF amplitude was studied by Katouzian et al [4] and Roodaki et al [15]. Recently, Ciompi et al [1] presented a method for plaque characterization that enhances in-vitro training sets by including examples from in-vivo coronary plaques using a floating forward feature selection method.…”

Section: Introductionmentioning

confidence: 99%

Towards Extra-Luminal Blood Detection from Intravascular Ultrasound Radio Frequency Data

Mendizabal-Ruiz

Biros

Kakadiaris

2011

Lecture Notes in Computer Science

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Abstract. Recent evidence has suggested that the presence and proliferation of vasa vasorum (VV) in the plaque is correlated to an increase in plaque inflammation and destabilization, leading to acute coronary events (e.g., heart attacks). Therefore, the detection and quantification of VV in plaque (i.e., extra luminal blood perfusion) is an important problem since it may enable the development of an index of plaque vulnerability. In this paper, we explore the feasibility of a method that employs a physics-based model of the scattered intravascular ultrasound (IVUS) radio frequency signal for the detection of blood. We evaluate our method using synthetic data and validate it using six 40 MHz pullback sequences acquired with three different IVUS systems from different arteries of rabbits and swines. Our experimental results are very promising and indicate the feasibility of our method for the computation of a feature that leads to automatic extra-luminal blood detection which may be an indication of plaque inflammation.

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Cardiovascular Informatics: A Perspective on Promises and Challenges of IVUS Data Analysis

Kakadiaris

Ruiz

2012

Optimization and Data Analysis in Biomedical Informatics

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Modified wavelet transform features for characterizing different plaque types in IVUS images; A feasibility study

Abstract: Abstract

Cited by 6 publications

References 10 publications

An Inverse Scattering Algorithm for the Segmentation of the Luminal Border on Intravascular Ultrasound Data

An Inverse Scattering Algorithm for the Segmentation of the Luminal Border on Intravascular Ultrasound Data

Towards Extra-Luminal Blood Detection from Intravascular Ultrasound Radio Frequency Data

Cardiovascular Informatics: A Perspective on Promises and Challenges of IVUS Data Analysis

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