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Title:

Deep learning derived tumor infiltration maps for personalized target definition in Glioblastoma radiotherapy.

Document type:
Journal Article
Author(s):
Peeken, Jan C; Molina-Romero, Miguel; Diehl, Christian; Menze, Bjoern H; Straube, Christoph; Meyer, Bernhard; Zimmer, Claus; Wiestler, Benedikt; Combs, Stephanie E
Abstract:
PURPOSE: Glioblastoma is routinely treated by concomitant radiochemotherapy. Current target definition guidelines use anatomic MRI (magnetic resonance imaging) scans, taking into account contrast enhancement and the rather unspecific hyperintensity on the fluid-attenuated inversion recovery (FLAIR) sequence. METHODS AND MATERIALS: We applied deep learning based free water correction of diffusion tensor imaging (DTI) scans to estimate the infiltrative gross tumor volume (iGTV) inside of the FLAIR...     »
Journal title abbreviation:
Radiother Oncol
Year:
2019
Journal volume:
138
Pages contribution:
166-172
Fulltext / DOI:
doi:10.1016/j.radonc.2019.06.031
Pubmed ID:
http://view.ncbi.nlm.nih.gov/pubmed/31302391
Print-ISSN:
0167-8140
TUM Institution:
Fachgebiet Neuroradiologie (Prof. Zimmer); Klinik und Poliklinik für RadioOnkologie und Strahlentherapie; Neurochirurgische Klinik und Poliklinik
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