Quantitative Texture Analysis and Transesophageal Echocardiography to Characterize the Acute Myocardial Contusion

Amichi, Abdelaziz; Laugier, Pascal

doi:10.2174/1874431100903010013

TOMINFOJ

2009

DOI: 10.2174/1874431100903010013

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Quantitative Texture Analysis and Transesophageal Echocardiography to Characterize the Acute Myocardial Contusion

Abdelaziz Amichi

Pascal Laugier²

Abstract: Myocardial contusion (MC) is a common injury following blunt chest trauma without any specific symptoms.Several techniques such as electrocardiogram, estimation of myocardial band fraction of creatine phosphokinase, chest radiography and the scintiscanning missed efficiency to characterize the MC.Another technique based on transesophageal echocardiography [TEE] allows to visualize the structures of the heart with a good spatial resolution.We postulated that the quantitative texture analysis of regional image … Show more

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Cited by 3 publications

References 24 publications

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Automated Identification of Infarcted Myocardium Tissue Characterization Using Ultrasound Images: A Review

Sudarshan

Acharya

et al. 2015

IEEE Rev. Biomed. Eng.

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Myocardial infarction (MI) or acute myocardial infarction commonly known as heart attack is one of the major causes of cardiac death worldwide. It occurs when the blood supply to the portion of the heart muscle is blocked or stopped causing death of heart muscle cells. Early detection of MI will help to prevent the infarct expansion leading to left ventricle (LV) remodeling and further damage to the cardiac muscles. Timely identification of MI and the extent of LV remodeling are crucial to reduce the time taken for further tests, and save the cost due to early treatment. Echocardiography images are widely used to assess the differential diagnosis of normal and infarcted myocardium. The reading of ultrasound images is subjective due to interobserver variability and may lead to inconclusive findings which may increase the anxiety for patients. Hence, a computer-aided diagnostic (CAD) technique which uses echocardiography images of the heart coupled with pattern recognition algorithms can accurately classify normal and infarcted myocardium images. In this review paper, we have discussed the various components that are used to develop a reliable CAD system.

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Automated Identification of Infarcted Myocardium Tissue Characterization Using Ultrasound Images: A Review

Sudarshan

Acharya

et al. 2015

IEEE Rev. Biomed. Eng.

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Texture Spectrum Coupled with Entropy and Homogeneity Image Features for Myocardium Muscle Characterization

Moraru

Moldovanu

Culea-Florescu

et al. 2019

CBIO

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Background: People in middle/later age often suffer from heart muscle damage due to coronary artery disease associated to myocardial infarction. In young people, the genetic forms of cardiomyopathies (heart muscle disease) are the utmost protuberant cause of myocardial disease. Objective: Accurate early detected information regarding the myocardial tissue structure is a key answer for tracking the progress of several myocardial diseases. associations while known disease-lncRNA associations are required only. Method: The present work proposes a new method for myocardium muscle texture classification based on entropy, homogeneity and on the texture unit-based texture spectrum approaches. Entropy and homogeneity are generated in moving windows of size 3x3 and 5x5 to enhance the texture features and to create the premise of differentiation of the myocardium structures. The texture is then statistically analyzed using the texture spectrum approach. Texture classification is achieved based on a fuzzy c–means descriptive classifier. The proposed method has been tested on a dataset of 80 echocardiographic ultrasound images in both short-axis and long-axis in apical two chamber view representations, for normal and infarct pathologies. Results: The noise sensitivity of the fuzzy c–means classifier was overcome by using the image features. The results established that the entropy-based features provided superior clustering results compared to homogeneity. Conclusion: Entropy image feature has a lower spread of the data in the clusters of healthy subjects and myocardial infarction. Also, the Euclidean distance function between the cluster centroids has higher values for both LAX and SAX views for entropy images.</P>

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Cardiac MRI Radiomics: review

Maksimova,

Ussov,

Shelkovnikova

et al. 2023

SJCEM

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A study of foreign and domestic literature devoted to the application of texture analysis of magnetic resonance images of the heart was performed. The analysis included publications selected by key words and their combinations: cardiac magnetic resonance imaging (MRI), myocarditis, myocardial infarction, cardiomyopathy, radiomics, and texture analysis. Radiomics and texture analysis, as a new and rapidly developing direction of in-depth analysis of digital medical images, is developing, the number of publications on this topic is growing every year and the topic is not losing its relevance. Radiomics is a promising method of image analysis that aims to improve the diagnosis and prognosis of diseases by extracting a large number of quantitative features that can be missed by the human eye in the visual analysis of images. Radiomics biomarkers derived by extracting data from magnetic resonance images of the heart could be a valuable tool for assessing myocardial viability, myocardial lesions in myocarditis and cardiomyopathies.

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Quantitative Texture Analysis and Transesophageal Echocardiography to Characterize the Acute Myocardial Contusion

Cited by 3 publications

References 24 publications

Automated Identification of Infarcted Myocardium Tissue Characterization Using Ultrasound Images: A Review

Automated Identification of Infarcted Myocardium Tissue Characterization Using Ultrasound Images: A Review

Texture Spectrum Coupled with Entropy and Homogeneity Image Features for Myocardium Muscle Characterization

Cardiac MRI Radiomics: review

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