Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis

Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis

<b>Purpose:</b> Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective study was to improve im...

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Bibliographic Details
Main Authors: Felix Kubicka, Qinxuan Tan, Tom Meyer, Dominik Nickel, Elisabeth Weiland, Moritz Wagner, Stephan Rodrigo Marticorena Garcia
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Current Oncology
Subjects:
MRI
deep learning
thin slice
HASTE
abdomen
high resolution
Online Access:https://www.mdpi.com/1718-7729/32/1/30
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