工作流程
磁共振成像
计算机科学
转化(遗传学)
医学物理学
人工智能
数据挖掘
数据科学
医学
放射科
生物
生物化学
数据库
基因
作者
Tom Hilbert,Patrick Omoumi,Marcus Raudner,Tobias Kober
标识
DOI:10.1097/rli.0000000000000917
摘要
This review summarizes the existing techniques and methods used to generate synthetic contrasts from magnetic resonance imaging data focusing on musculoskeletal magnetic resonance imaging. To that end, the different approaches were categorized into 3 different methodological groups: mathematical image transformation, physics-based, and data-driven approaches. Each group is characterized, followed by examples and a brief overview of their clinical validation, if present. Finally, we will discuss the advantages, disadvantages, and caveats of synthetic contrasts, focusing on the preservation of image information, validation, and aspects of the clinical workflow.
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