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Titel:

Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas.

Dokumenttyp:
Journal Article
Autor(en):
Eichinger, Paul; Alberts, Esther; Delbridge, Claire; Trebeschi, Stefano; Valentinitsch, Alexander; Bette, Stefanie; Huber, Thomas; Gempt, Jens; Meyer, Bernhard; Schlegel, Juergen; Zimmer, Claus; Kirschke, Jan S; Menze, Bjoern H; Wiestler, Benedikt
Abstract:
We hypothesized that machine learning analysis based on texture information from the preoperative MRI can predict IDH mutational status in newly diagnosed WHO grade II and III gliomas. This retrospective study included in total 79 consecutive patients with a newly diagnosed WHO grade II or III glioma. Local binary pattern texture features were generated from preoperative B0 and fractional anisotropy (FA) diffusion tensor imaging. Using a training set of 59 patients, a single hidden layer neural...     »
Zeitschriftentitel:
Sci Rep
Jahr:
2017
Band / Volume:
7
Heft / Issue:
1
Seitenangaben Beitrag:
13396
Sprache:
eng
Volltext / DOI:
doi:10.1038/s41598-017-13679-4
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/29042619
Print-ISSN:
2045-2322
TUM Einrichtung:
Fachgebiet Neuroradiologie (Prof. Zimmer); Neurochirurgische Klinik und Poliklinik
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