Deep Learning-Based Denoising of CEST MR Data: A Feasibility Study on Applying Synthetic Phantoms in Medical Imaging

Deep Learning-Based Denoising of CEST MR Data: A Feasibility Study on Applying Synthetic Phantoms in Medical Imaging

Chemical Exchange Saturation Transfer (CEST) magnetic resonance imaging (MRI) provides a novel method for analyzing biomolecule concentrations in tissues without exogenous contrast agents. Despite its potential, achieving a high signal-to-noise ratio (SNR) is imperative for detecting small CEST effe...

وصف كامل

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Karl Ludger Radke, Benedikt Kamp, Vibhu Adriaenssens, Julia Stabinska, Patrik Gallinnis, Hans-Jörg Wittsack, Gerald Antoch, Anja Müller-Lutz
التنسيق: مقال
اللغة:English
منشور في: MDPI AG 2023-10-01
سلاسل:Diagnostics
الموضوعات:
CEST
deep learning
synthetic phantoms
noise detection
noise reduction
noise suppression
الوصول للمادة أونلاين:https://www.mdpi.com/2075-4418/13/21/3326

الانترنت

https://www.mdpi.com/2075-4418/13/21/3326

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