Literature DB >> 1651341

Quantitative texture analysis in echocardiography: application to the diagnosis of myocarditis.

E M Ferdeghini1, B Pinamonti, E Picano, F Lattanzi, R Bussani, G Slavich, A Benassi, F Camerini, L Landini, A L'Abbate.   

Abstract

Altered myocardial texture associated with inflammatory infiltration or fibrosis of the myocardium has already been described using qualitative and subjective analysis of two-dimensional echocardiograms. The aim of this work is to test whether quantitative analysis of regional image texture in two-dimensional echocardiograms would be an accurate method to identify myocarditis and myocardial fibrosis. A set of 20 two-dimensional studies with endomyocardial biopsy evaluation was examined in 13 patients. Biopsy-proven myocarditis was present in 8 studies; myocarditis and fibrosis in 4; fibrosis in 3; healing/healed myocarditis in 5. A control group of 8 normal subjects was also studied by echocardiography. After quantitative texture analysis of the first order, entropy appeared to consistently differentiate myocarditis from controls. Among second-order parameters, patients affected by myocarditis or fibrosis showed a decreased entropy and higher angular second moment versus controls. We conclude that myocarditis and fibrosis induce similar image texture alterations in ultrasonic images, with increased spatial heterogeneity of the gray level distribution, which can be differentiated from normal structures with digital image analysis techniques.

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Year:  1991        PMID: 1651341     DOI: 10.1002/jcu.1870190503

Source DB:  PubMed          Journal:  J Clin Ultrasound        ISSN: 0091-2751            Impact factor:   0.910


  3 in total

1.  Texture analysis of protein distribution images to find differences due to aging and superfusion.

Authors:  S Dutta; B J Barber; S Parameswaran
Journal:  Ann Biomed Eng       Date:  1995 Nov-Dec       Impact factor: 3.934

Review 2.  Viral myocarditis and dilated cardiomyopathy: mechanisms, manifestations, and management.

Authors:  M T Kearney; J M Cotton; P J Richardson; A M Shah
Journal:  Postgrad Med J       Date:  2001-01       Impact factor: 2.401

3.  Automated classification of dense calcium tissues in gray-scale intravascular ultrasound images using a deep belief network.

Authors:  Juhwan Lee; Yoo Na Hwang; Ga Young Kim; Ji Yean Kwon; Sung Min Kim
Journal:  BMC Med Imaging       Date:  2019-12-30       Impact factor: 1.930

  3 in total

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