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Titel:

Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor Models.

Dokumenttyp:
Journal Article
Autor(en):
Ezhov, Ivan; Mot, Tudor; Shit, Suprosanna; Lipkova, Jana; Paetzold, Johannes C; Kofler, Florian; Pellegrini, Chantal; Kollovieh, Marcel; Navarro, Fernando; Li, Hongwei; Metz, Marie; Wiestler, Benedikt; Menze, Bjoern
Abstract:
Modeling of brain tumor dynamics has the potential to advance therapeutic planning. Current modeling approaches resort to numerical solvers that simulate the tumor progression according to a given differential equation. Using highly-efficient numerical solvers, a single forward simulation takes up to a few minutes of compute. At the same time, clinical applications of tumor modeling often imply solving an inverse problem, requiring up to tens of thousands of forward model evaluations when used f...     »
Zeitschriftentitel:
IEEE Trans Med Imaging
Jahr:
2022
Band / Volume:
41
Heft / Issue:
5
Seitenangaben Beitrag:
1269-1278
Volltext / DOI:
doi:10.1109/TMI.2021.3136582
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/34928790
Print-ISSN:
0278-0062
TUM Einrichtung:
Klinik und Poliklinik für RadioOnkologie und Strahlentherapie (Prof. Combs); Professur für AI for Image-Guided Diagnosis and Therapy (Prof. Wiestler); Professur für Neuroradiologie (Prof. Zimmer)
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