Validation of a deep learning-based software for automated analysis of T2 mapping in cardiac magnetic resonance imaging.

Hwan Kim¹, Young Joong Yang², Kyunghwa Han¹, Pan Ki Kim², Byoung Wook Choi^1,2, Jin Young Kim³, Young Joo Suh¹

¹Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea.

²Phantomics Co., Ltd., Seoul, Korea.

³Department of Radiology, Dongsan Hospital, Keimyung University College of Medicine, Daegu, Korea.

PubMed PMC DOI PDF

Abstract

BACKGROUND: The reliability and diagnostic performance of deep learning (DL)-based automated T2 measurements on T2 map of 3.0-T cardiac magnetic resonance imaging (MRI) using multi-institutional datasets have not been investigated. We aimed to evaluate the performance of a DL-based software for measuring automated T2 values from 3.0-T cardiac MRI obtained at two centers. METHODS: Eighty-three sub…

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