Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

Bauer, Stefan; Seiler, Christof; Bardyn, Thibaut; Buechler, Philippe; Reyes, Mauricio (2010). Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration. In: 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2010 (pp. 4080-4083). IEEE 10.1109/IEMBS.2010.5627302

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We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Bauer, Stefan; Seiler, Christof; Bardyn, Thibaut; Büchler, Philippe and Reyes, Mauricio

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

ISBN:

978-1-4244-4123-5

Publisher:

IEEE

Language:

English

Submitter:

Mauricio Antonio Reyes Aguirre

Date Deposited:

04 Oct 2013 14:08

Last Modified:

08 Jun 2016 10:19

Publisher DOI:

10.1109/IEMBS.2010.5627302

PubMed ID:

21096622

Web of Science ID:

000287964004120

BORIS DOI:

10.7892/boris.564

URI:

https://boris.unibe.ch/id/eprint/564 (FactScience: 199773)

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