Automated Diagnosis and Assessment of Cardiac Structural Alteration in Hypertension Ultrasound Images.


Journal

Contrast media & molecular imaging
ISSN: 1555-4317
Titre abrégé: Contrast Media Mol Imaging
Pays: England
ID NLM: 101286760

Informations de publication

Date de publication:
2022
Historique:
received: 13 04 2022
revised: 28 04 2022
accepted: 09 05 2022
entrez: 10 6 2022
pubmed: 11 6 2022
medline: 14 6 2022
Statut: epublish

Résumé

Hypertension (HTN) is a major risk factor for cardiovascular diseases. At least 45% of deaths due to heart disease and 51% of deaths due to stroke are the result of hypertension. According to research on the prevalence and absolute burden of HTN in India, HTN positively correlated with age and was present in 20.6% of men and 20.9% of women. It was estimated that this trend will increase to 22.9% and 23.6% for men and women, respectively, by 2025. Controlling blood pressure is therefore important to lower both morbidity and mortality. Computer-aided diagnosis (CAD) is a noninvasive technique which can determine subtle myocardial structural changes at an early stage. In this work, we show how a multi-resolution analysis-based CAD system can be utilized for the detection of early HTN-induced left ventricular heart muscle changes with the help of ultrasound imaging. Firstly, features were extracted from the ultrasound imagery, and then the feature dimensions were reduced using a locality sensitive discriminant analysis (LSDA). The decision tree classifier with contourlet and shearlet transform features was later employed for improved performance and maximized accuracy using only two features. The developed model is applicable for the evaluation of cardiac structural alteration in HTN and can be used as a standalone tool in hospitals and polyclinics.

Identifiants

pubmed: 35685669
doi: 10.1155/2022/5616939
pmc: PMC9168207
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5616939

Informations de copyright

Copyright © 2022 U. Raghavendra et al.

Déclaration de conflit d'intérêts

The authors declare that they have no conflicts of interest.

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Auteurs

U Raghavendra (U)

Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.

Joel Koh En Wei (JK)

Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore 599489, Singapore.

Anjan Gudigar (A)

Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.

Akanksha Shetty (A)

Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India.

Jyothi Samanth (J)

Department of Cardiovascular Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal 576104, India.

Ganesh Paramasivam (G)

Department of Cardiology, Kasturba Medical College and Hospital, Manipal Academy of Higher Education, Manipal 576104, India.

Sujay Jagadish (S)

Department of Cardiology, Kasturba Medical College and Hospital, Manipal Academy of Higher Education, Manipal 576104, India.

Nahrizul Adib Kadri (NA)

Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.

Murat Karabatak (M)

Department of Software Engineering, Firat University, Elazig, Turkey.

Özal Yildirim (Ö)

Department of Software Engineering, Firat University, Elazig, Turkey.

N Arunkumar (N)

Department of Biomedical Engineering, Rathinam College of Engineering, Coimbatore, India.

Ali Abbasian Ardakani (AA)

Department of Radiology Technology, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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