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Journal of Medical Imaging

Locally adaptive magnetic resonance intensity models for unsupervised segmentation of multiple sclerosis lesions
Author(s): Alfiia Galimzianova; Ziga Lesjak; Daniel L. Rubin; Boštjan Likar; Franjo Pernuš; Žiga Špiclin
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Paper Abstract

Multiple sclerosis (MS) is a neurological disease characterized by focal lesions and morphological changes in the brain captured on magnetic resonance (MR) images. However, extraction of the corresponding imaging markers requires accurate segmentation of normal-appearing brain structures (NABS) and the lesions in MR images. On MR images of healthy brains, the NABS can be accurately captured by MR intensity mixture models, which, in combination with regularization techniques, such as in Markov random field (MRF) models, are known to give reliable NABS segmentation. However, on MR images that also contain abnormalities such as MS lesions, obtaining an accurate and reliable estimate of NABS intensity models is a challenge. We propose a method for automated segmentation of normal-appearing and abnormal structures in brain MR images that is based on a locally adaptive NABS model, a robust model parameters estimation method, and an MRF-based segmentation framework. Experiments on multisequence brain MR images of 30 MS patients show that, compared to whole-brain MR intensity model and compared to four popular unsupervised lesion segmentation methods, the proposed method increases the accuracy of MS lesion segmentation.

Paper Details

Date Published: 1 November 2017
PDF: 11 pages
J. Med. Imag. 5(1) 011007 doi: 10.1117/1.JMI.5.1.011007
Published in: Journal of Medical Imaging Volume 5, Issue 1
Show Author Affiliations
Alfiia Galimzianova, Univ. of Ljubljana (Slovenia)
Stanford Univ. School of Medicine (United States)
Ziga Lesjak, Univ. of Ljubljana (Slovenia)
Daniel L. Rubin, Stanford Univ. (United States)
Boštjan Likar, Univ. of Ljubljana (Slovenia)
Sensum d.o.o. Computer Vision Systems (Slovenia)
Franjo Pernuš, Univ. of Ljubljana (Slovenia)
Žiga Špiclin, Univ. of Ljubljana (Slovenia)
Sensum d.o.o. Computer Vision Systems (Slovenia)

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