Literature DB >> 10048846

Tissue characterization in intravascular ultrasound images.

X Zhang1, C R McKay, M Sonka.   

Abstract

Intravascular ultrasound (IVUS) imaging permits direct visualization of vascular pathology. It has been used to evaluate lumen and plaque in coronary arteries and its clinical significance for guidance of coronary interventions is increasingly recognized. Conventional manual evaluation is tedious and time-consuming. This paper describes a highly automated approach to segmentation of coronary wall and plaque, and determination of plaque composition in individual IVUS images and pullback image sequences. The determined regions of plaque were classified in one of three classes: soft plaque, hard plaque, or hard plaque shadow. The method's performance was assessed in vitro and in vivo in comparison with observer-defined independent standards. In the analyzed images and image sequences, the mean border positioning error of the wall and plaque borders ranged from 0.13-0.17 mm. Plaque classification correctness was 90%.

Mesh:

Year:  1998        PMID: 10048846     DOI: 10.1109/42.746622

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  14 in total

Review 1.  Biplane X-ray angiograms, intravascular ultrasound, and 3D visualization of coronary vessels.

Authors:  K R Hoffmann; A Wahle; C Pellot-Barakat; J Sklansky; M Sonka
Journal:  Int J Card Imaging       Date:  1999-12

2.  Validation of an automated system for luminal and medial-adventitial border detection in three-dimensional intravascular ultrasound.

Authors:  Jon D Klingensmith; E Murat Tuzcu; Steven E Nissen; D Geoffrey Vince
Journal:  Int J Cardiovasc Imaging       Date:  2003-04       Impact factor: 2.357

3.  Plaque development, vessel curvature, and wall shear stress in coronary arteries assessed by X-ray angiography and intravascular ultrasound.

Authors:  Andreas Wahle; John J Lopez; Mark E Olszewski; Sarah C Vigmostad; Krishnan B Chandran; James D Rossen; Milan Sonka
Journal:  Med Image Anal       Date:  2006-04-27       Impact factor: 8.545

4.  Optimal surface segmentation in volumetric images--a graph-theoretic approach.

Authors:  Kang Li; Xiaodong Wu; Danny Z Chen; Milan Sonka
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2006-01       Impact factor: 6.226

5.  Fusing in-vitro and in-vivo intravascular ultrasound data for plaque characterization.

Authors:  Francesco Ciompi; Oriol Pujol; Carlo Gatta; Oriol Rodríguez-Leor; Josepa Mauri-Ferré; Petia Radeva
Journal:  Int J Cardiovasc Imaging       Date:  2009-11-29       Impact factor: 2.357

6.  Moment-based texture segmentation of luminal contour in intravascular ultrasound images.

Authors:  Esmeraldo Dos Santos Filho; Makoto Yoshizawa; Akira Tanaka; Yoshifumi Saijo; Takahiro Iwamoto
Journal:  J Med Ultrason (2001)       Date:  2005-09       Impact factor: 1.314

7.  A Domain Enriched Deep Learning Approach to Classify Atherosclerosis using Intravascular Ultrasound Imaging.

Authors:  Max L Olender; Lambros S Athanasiou; Lampros K Michalis; Dimitris I Fotiadis; Elazer R Edelman
Journal:  IEEE J Sel Top Signal Process       Date:  2020-06-15       Impact factor: 6.856

8.  Three methods for accurate quantification of plaque volume in coronary arteries.

Authors:  Ruben Medina; Andreas Wahle; Mark E Olszewski; Milan Sonka
Journal:  Int J Cardiovasc Imaging       Date:  2003-08       Impact factor: 2.357

9.  Segmentation of wall and plaque in in vitro vascular MR images.

Authors:  Fuxing Yang; Gerhard Holzapfel; Christian Schulze-Bauer; Rudolf Stollberger; Daniel Thedens; Lizann Bolinger; Alan Stolpen; Milan Sonka
Journal:  Int J Cardiovasc Imaging       Date:  2003-10       Impact factor: 2.357

Review 10.  Recent trends in coronary intravascular ultrasound: tracking atherosclerosis, pursuit of vulnerable plaques, and beyond.

Authors:  Ilke Sipahi; Stephen J Nicholls; E Murat Tuzcu
Journal:  J Nucl Cardiol       Date:  2006 Jan-Feb       Impact factor: 5.952

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