Literature DB >> 20442021

Intima-media thickness: setting a standard for a completely automated method of ultrasound measurement.

Filippo Molinari1, Guang Zeng, Jasjit S Suri.   

Abstract

The intima-media thickness (IMT) of the common carotid artery is a widely used clinical marker of severe cardiovascular diseases. IMT is usually manually measured on longitudinal B-mode ultrasound images. Many computer-based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. Most of these, however, require a certain degree of user interaction. In this paper we describe a new, completely automated layer extraction technique (named CALEXia) for the segmentation and IMT measurement of the carotid wall in ultrasound images. CALEXia is based on an integrated approach consisting of feature extraction, line fitting, and classification that enables the automated tracing of the carotid adventitial walls. IMT is then measured by relying on a fuzzy K-means classifier. We tested CALEXia on a database of 200 images. We compared CALEXia?s performance with those of a previously developed methodology that was based on signal analysis (CULEXsa). Three trained operators manually segmented the images and the average profiles were considered as the ground truth. The average error from CALEXia for lumen-intima (LI) and media- adventitia (MA) interface tracings were 1.46 +/- 1.51 pixel (0.091 +/- 0.093 mm) and 0.40 +/- 0.87 pixel (0.025 +/- 0.055 mm), respectively. The corresponding errors for CULEXsa were 0.55 +/- 0.51 pixels (0.035 +/- 0.032 mm) and 0.59 +/- 0.46 pixels (0.037 +/- 0.029 mm). The IMT measurement error was equal to 0.87 +/- 0.56 pixel (0.054 +/- 0.035 mm) for CALEXia and 0.12 +/- 0.14 pixel (0.01 +/- 0.01 mm) for CULEXsa. Thus, CALEXia showed limited performance in segmenting the LI interface, but outperformed CULEXsa in the MA interface and in the number of images correctly processed (190 for CALEXia and 184 for CULEXsa). Based upon two complementary strategies, we anticipate fusing them for further IMT improvements.

Entities:  

Mesh:

Year:  2010        PMID: 20442021     DOI: 10.1109/TUFFC.2010.1522

Source DB:  PubMed          Journal:  IEEE Trans Ultrason Ferroelectr Freq Control        ISSN: 0885-3010            Impact factor:   2.725


  18 in total

1.  Automatic segmentation of carotid B-mode images using fuzzy classification.

Authors:  Rui Rocha; Jorge Silva; Aurélio Campilho
Journal:  Med Biol Eng Comput       Date:  2012-03-14       Impact factor: 2.602

2.  Inter-greedy technique for fusion of different segmentation strategies leading to high-performance carotid IMT measurement in ultrasound images.

Authors:  Filippo Molinari; Guang Zeng; Jasjit S Suri
Journal:  J Med Syst       Date:  2010-05-08       Impact factor: 4.460

3.  CAUDLES-EF: carotid automated ultrasound double line extraction system using edge flow.

Authors:  Filippo Molinari; Kristen M Meiburger; Guang Zeng; Andrew Nicolaides; Jasjit S Suri
Journal:  J Digit Imaging       Date:  2011-12       Impact factor: 4.056

4.  Completely automated robust edge snapper for carotid ultrasound IMT measurement on a multi-institutional database of 300 images.

Authors:  Filippo Molinari; U Rajendra Acharya; Guang Zeng; Kristen M Meiburger; Jasjit S Suri
Journal:  Med Biol Eng Comput       Date:  2011-04-21       Impact factor: 2.602

5.  Plaque Tissue Morphology-Based Stroke Risk Stratification Using Carotid Ultrasound: A Polling-Based PCA Learning Paradigm.

Authors:  Luca Saba; Pankaj K Jain; Harman S Suri; Nobutaka Ikeda; Tadashi Araki; Bikesh K Singh; Andrew Nicolaides; Shoaib Shafique; Ajay Gupta; John R Laird; Jasjit S Suri
Journal:  J Med Syst       Date:  2017-05-13       Impact factor: 4.460

Review 6.  A Special Report on Changing Trends in Preventive Stroke/Cardiovascular Risk Assessment Via B-Mode Ultrasonography.

Authors:  Ankush Jamthikar; Deep Gupta; Narendra N Khanna; Tadashi Araki; Luca Saba; Andrew Nicolaides; Aditya Sharma; Tomaz Omerzu; Harman S Suri; Ajay Gupta; Sophie Mavrogeni; Monika Turk; John R Laird; Athanasios Protogerou; Petros P Sfikakis; George D Kitas; Vijay Viswanathan; Gyan Pareek; Martin Miner; Jasjit S Suri
Journal:  Curr Atheroscler Rep       Date:  2019-05-01       Impact factor: 5.113

7.  Automated carotid IMT measurement and its validation in low contrast ultrasound database of 885 patient Indian population epidemiological study: results of AtheroEdge™ Software.

Authors:  F Molinari; K M Meiburger; G Zeng; L Saba; U Rajendra Acharya; L Famiglietti; N Georgiou; A Nicolaides; R Sriswan Mamidi; H Kuper; J S Suri
Journal:  Int Angiol       Date:  2012-02       Impact factor: 2.789

8.  Automatic detection of the intima-media thickness in ultrasound images of the common carotid artery using neural networks.

Authors:  Rosa-María Menchón-Lara; María-Consuelo Bastida-Jumilla; Juan Morales-Sánchez; José-Luis Sancho-Gómez
Journal:  Med Biol Eng Comput       Date:  2013-11-27       Impact factor: 2.602

Review 9.  A Review on Carotid Ultrasound Atherosclerotic Tissue Characterization and Stroke Risk Stratification in Machine Learning Framework.

Authors:  Aditya M Sharma; Ajay Gupta; P Krishna Kumar; Jeny Rajan; Luca Saba; Ikeda Nobutaka; John R Laird; Andrew Nicolades; Jasjit S Suri
Journal:  Curr Atheroscler Rep       Date:  2015-09       Impact factor: 5.113

10.  A low-cost machine learning-based cardiovascular/stroke risk assessment system: integration of conventional factors with image phenotypes.

Authors:  Ankush Jamthikar; Deep Gupta; Narendra N Khanna; Luca Saba; Tadashi Araki; Klaudija Viskovic; Harman S Suri; Ajay Gupta; Sophie Mavrogeni; Monika Turk; John R Laird; Gyan Pareek; Martin Miner; Petros P Sfikakis; Athanasios Protogerou; George D Kitas; Vijay Viswanathan; Andrew Nicolaides; Deepak L Bhatt; Jasjit S Suri
Journal:  Cardiovasc Diagn Ther       Date:  2019-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.