Fully Automated, Quality-Controlled Cardiac Analysis From CMR Validation and Large-Scale Application to Characterize Cardiac Function

Ruijsink, B; Puyol-Antón, E; Oksuz, İlkay; Sinclair, M; Bai, W; Schnabel, JA; Razavi, R; King, AP

doi:10.1016/j.jcmg.2019.05.030

Fully Automated, Quality-Controlled Cardiac Analysis From CMR Validation and Large-Scale Application to Characterize Cardiac Function

Atıf İçin Kopyala

Ruijsink B., Puyol-Antón E., Oksuz İ., Sinclair M., Bai W., Schnabel J., ...Daha Fazla

JACC-CARDIOVASCULAR IMAGING, cilt.13, sa.3, ss.684-695, 2020 (SCI-Expanded)

Yayın Türü: Makale / Tam Makale
Cilt numarası: 13 Sayı: 3
Basım Tarihi: 2020
Doi Numarası: 10.1016/j.jcmg.2019.05.030
Dergi Adı: JACC-CARDIOVASCULAR IMAGING
Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, EMBASE, MEDLINE
Sayfa Sayıları: ss.684-695
Anahtar Kelimeler: cardiac aging, cardiac function, cardiac magnetic resonance, CMR feature tracking, machine learning, quality control
İstanbul Teknik Üniversitesi Adresli: Hayır

Özet

OBJECTIVES This study sought to develop a fully automated framework for cardiac function analysis from cardiac magnetic resonance (CMR), including comprehensive quality control (QC) algorithms to detect erroneous output.