Automatic Segmentation of Brain Structures for Treatment Planning Optimization and Target Volume Definition

Autor:	Dimos Baltas, Thomas Bortfeld, Marco Langhans, Tobias Fechter, Harald Binder
Rok vydání:	2021
Předmět:	Computer science business.industry medicine.medical_treatment Deep learning Planning target volume Radiation therapy Market segmentation medicine Automatic segmentation Segmentation Computer vision Artificial intelligence Mr images business Radiation treatment planning
Zdroj:	Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data ISBN: 9783030718268 MICCAI (Challenges)
DOI:	10.1007/978-3-030-71827-5_5
Popis:	The MICCAI Challenge 2020 “Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Image” was about segmenting brain structures automatically for further use in the definition of the Clinical Target Volume (CTV) of glioblastoma patients and treatment planning optimization in radiation therapy. This paper describes the methods of the team “FREI”. A 3D U-Net style deep learning network was used to achieve human-like segmentation accuracy for most of the structures within seconds.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::38a9470f7dacc2c391b80757e1f43ef1 https://doi.org/10.1007/978-3-030-71827-5_5 Zobrazit plný text záznamu