Assessment of ventricular tachyarrhythmia in patients with hypertrophic cardiomyopathy with machine learning-based texture analysis of late gadolinium enhancement cardiac MRI

Alis, DENİZ; Guler, A.; Yergin, M.; Asmakutlu, O.

doi:10.1016/j.diii.2019.10.005

Assessment of ventricular tachyarrhythmia in patients with hypertrophic cardiomyopathy with machine learning-based texture analysis of late gadolinium enhancement cardiac MRI

Alis D. C., Guler A., Yergin M., Asmakutlu O.

DIAGNOSTIC AND INTERVENTIONAL IMAGING, cilt.101, sa.3, ss.137-146, 2020 (SCI-Expanded, Scopus)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 101 Sayı: 3
Basım Tarihi: 2020
Doi Numarası: 10.1016/j.diii.2019.10.005
Dergi Adı: DIAGNOSTIC AND INTERVENTIONAL IMAGING
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
Sayfa Sayıları: ss.137-146
Anahtar Kelimeler: Artificial intelligence, Cardiomyopathy, Hypertrophic, Machine learning, Tachycardia, Ventricular, Texture analysis, MYOCARDIAL SCAR, DIAGNOSIS, QUANTIFICATION, SEGMENTATION, ASSOCIATION, TACHYCARDIA, VALIDATION, CARDIOLOGY, CANCER, MAZDA
Acıbadem Mehmet Ali Aydınlar Üniversitesi Adresli: Evet

Özet

Objective: To assess the diagnostic value of machine learning-based texture feature analysis of late gadolinium enhancement images on cardiac magnetic resonance imaging (MRI) for assessing the presence of ventricular tachyarrhythmia (VT) in patients with hypertrophic cardiomyopathy.