Mumford-Shah based unsupervised segmentation of brain tissue on MR images

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Automated segmentation of different tissues on medical images is a crucial concept for medical image analysis. In this study, unsupervised image segmentation problem is generalized as a Mumford-Shah energy minimization problem, and several solution proposals for the problem are investigated. Ambrosio-Tortorelli approximation method is implemented, and the performance of the algorithm on magnetic resonance (MR) images of brain is evaluated. First image used in the experiments is chosen among the ones which contain an edema formation due to a brain tumor, and the second one belongs to a healthy subject on which gray matter/white matter segmentation is aimed. Acquired results are presented in visual, tabular and numerical forms. Results and performance are discussed and quantitatively evaluated. © Springer International Publishing Switzerland 2014.

Cite

CITATION STYLE

APA

Cevik, A., & Eyuboglu, B. M. (2014). Mumford-Shah based unsupervised segmentation of brain tissue on MR images. In IFMBE Proceedings (Vol. 41, pp. 265–268). Springer Verlag. https://doi.org/10.1007/978-3-319-00846-2_66

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free