Deep learning reconstruction for zero echo time lung magnetic resonance imaging: impact on image quality and lesion detection.

Journal: Clinical radiology

Published Date: Jul 17, 2024

AIMS: This study aimed to examine the impact of deep-learning reconstruction (DLR) on zero echo time (ZTE) lung MRI.

K Bae

Department of Radiology, Gyeongsang National University Changwon Hospital, 11 Samjeongja-ro, Changwon, Republic of Korea; Department of Radiology, Institute of Medical Science, Gyeongsang National University School of Medicine, 816-15 Jinju-daero, Jinju, Republic of Korea. Electronic address: ksbae@gnu.ac.kr.
J Lee
Y Jung

GE HealthCare, 416 Hangang-daero, Seoul, Republic of Korea. Electronic address: yunsubjung9909@gmail.com.
J de Arcos

GE HealthCare, Amersham Place, Little Chalfont, United Kingdom. Electronic address: Jose.deArcos@gehealthcare.com.
K N Jeon

Department of Radiology, Gyeongsang National University Changwon Hospital, 11 Samjeongja-ro, Changwon, Republic of Korea; Department of Radiology, Institute of Medical Science, Gyeongsang National University School of Medicine, 816-15 Jinju-daero, Jinju, Republic of Korea. Electronic address: knjeon@gnu.ac.kr.

Adult Aged Deep Learning Female Humans Image Interpretation, Computer-Assisted Lung Lung Neoplasms Magnetic Resonance Imaging Male Middle Aged Phantoms, Imaging Retrospective Studies Tomography, X-Ray Computed

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