A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning

Author:

Agn Mikael,Munck af Rosenschöld PerORCID,Puonti Oula,Lundemann Michael J.ORCID,Mancini Laura,Papadaki Anastasia,Thust Steffi,Ashburner John,Law Ian,Van Leemput Koen

Funder

NCRR

NIBIB

Lundbeck foundation

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference78 articles.

1. A generative model for segmentation of tumor and organs-at-risk for radiation therapy planning of glioblastoma patients;Agn,2016

2. Brain tumor segmentation using a generative model with an rbm prior on tumor shape;Agn,2016

3. Image registration using a symmetric prior – in three dimensions;Ashburner;Hum. Brain. Mapp,2000

4. Glistrboost: combining multimodal mri segmentation, registration, and biophysical tumor growth modeling with gradient boosting machines for glioma segmentation;Bakas,2016

5. Integrated segmentation of brain tumor images for radiotherapy and neurosurgery;Bauer;Int. J. Imaging Syst. Technol.,2013

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