Titlebook: Glioma Imaging; Physiologic, Metabol Whitney B. Pope Book 2020 Springer Nature Switzerland AG 2020 glioma.brain tumor.neuroimaging.low grad

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,Exogene Einflüsse und Ovarialfunktion,genomics) that have clinical utility. While attempts have been made to visually decode various imaging features on MRIs of gliomas, an artificial intelligence approach is better suited to tease out pixel-level subtleties that may reflect different mutations. Machine learning, a form of artificial in

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Bildung, Freisetzung und Wirkung MR scanner systems and pulse sequence parameters for the same relative MR contrast (e.g., T1- or T2-“weighting”) can result in dramatic differences in perceived image contrast, leading to difficulty in interpretation of imaging results in multicenter clinical trials. Therefore, consensus recommenda

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https://doi.org/10.1007/978-3-030-27359-0glioma; brain tumor; neuroimaging; low grade glioma; radiogenomics; metabolic imaging

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Hormonal Regulation of Mammary Tumorsoma seen on routine MR imaging. Here we focus on physiologic and metabolic MR imaging techniques including diffusion, perfusion, and spectroscopy, as they relate to histopathology and molecular features of gliomas. The utility of these advanced techniques in evaluating glioma treatment response is also discussed.

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