Deep learning super-resolution magnetic resonance spectroscopic imaging of brain metabolism and mutant isocitrate dehydrogenase glioma.

Saved in:
Bibliographic Details
Title: Deep learning super-resolution magnetic resonance spectroscopic imaging of brain metabolism and mutant isocitrate dehydrogenase glioma.
Authors: Li X; A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA., Strasser B; A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA., Neuberger U; Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany., Vollmuth P; Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany., Bendszus M; Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany., Wick W; Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany., Dietrich J; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA., Batchelor TT; Department of Neurology, Brigham and Women Hospital, Harvard Medical School, Boston, Massachusetts, USA., Cahill DP; Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA., Andronesi OC; A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Source: Neuro-oncology advances [Neurooncol Adv] 2022 May 24; Vol. 4 (1), pp. vdac071. Date of Electronic Publication: 2022 May 24 (Print Publication: 2022).
Publication Type: Journal Article
Journal Info: Publisher: Oxford University Press Country of Publication: England NLM ID: 101755003 Publication Model: eCollection Cited Medium: Internet ISSN: 2632-2498 (Electronic) Linking ISSN: 26322498 NLM ISO Abbreviation: Neurooncol Adv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2632-2498
DOI:10.1093/noajnl/vdac071