Literature DB >> 19203880

A 3-D ultrasound-based framework to characterize the echo morphology of carotid plaques.

José C R Seabra1, Luís M Pedro, José Fernandes e Fernandes, João M Sanches.   

Abstract

Carotid atherosclerosis is the main cause of brain stroke, which is the most common life-threatening neurological disease. Nearly all methods aiming at assessing the risk of plaque rupture are based on its characterization from 2-D ultrasound images, which depends on plaque geometry, degree of stenosis, and echo morphology (intensity and texture). The computation of these indicators is, however, usually affected by inaccuracy and subjectivity associated with data acquisition and operator-dependent image selection. To circumvent these limitations, a novel and simple method based on 3-D freehand ultrasound is proposed that does not require any expensive equipment except the common scanner. This method comprises the 3-D reconstruction of carotids and plaques to provide clinically meaningful parameters not available in 2-D ultrasound imaging, namely diagnostic views not usually accessible via conventional techniques and local 3-D characterization of plaque echo morphology. The labeling procedure, based on graph cuts, allows us to identify, locate, and quantify potentially vulnerable foci within the plaque. Validation of the characterization method was made with synthetic data. Results of plaque characterization with real data are encouraging and consistent with the results from conventional methods and after inspection of surgically removed plaques.

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Year:  2009        PMID: 19203880     DOI: 10.1109/TBME.2009.2013964

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  4 in total

1.  Statistical 4D graphs for multi-organ abdominal segmentation from multiphase CT.

Authors:  Marius George Linguraru; John A Pura; Vivek Pamulapati; Ronald M Summers
Journal:  Med Image Anal       Date:  2012-02-11       Impact factor: 8.545

Review 2.  Multimodality carotid plaque tissue characterization and classification in the artificial intelligence paradigm: a narrative review for stroke application.

Authors:  Luca Saba; Skandha S Sanagala; Suneet K Gupta; Vijaya K Koppula; Amer M Johri; Narendra N Khanna; Sophie Mavrogeni; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; Durga P Misra; Vikas Agarwal; Aditya M Sharma; Vijay Viswanathan; Vijay S Rathore; Monika Turk; Raghu Kolluri; Klaudija Viskovic; Elisa Cuadrado-Godia; George D Kitas; Neeraj Sharma; Andrew Nicolaides; Jasjit S Suri
Journal:  Ann Transl Med       Date:  2021-07

3.  Image-based modeling and precision medicine: patient-specific carotid and coronary plaque assessment and predictions.

Authors:  Dalin Tang; Chun Yang; Jie Zheng; Gador Canton; Richard G Bach; Thomas S Hatsukami; Liang Wang; Deshan Yang; Kristen L Billiar; Chun Yuan
Journal:  IEEE Trans Biomed Eng       Date:  2013-01-25       Impact factor: 4.538

4.  Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images.

Authors:  Ran Zhou; Aaron Fenster; Yujiao Xia; J David Spence; Mingyue Ding
Journal:  Med Phys       Date:  2019-06-11       Impact factor: 4.071

  4 in total

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