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A hybrid approach to brain extraction from premature infant MRI

Péporté, Michèle, Ghita, Dana Ilea, Twomey, Eilish and Whelan, Paul F. ORCID: 0000-0001-9230-7656 (2011) A hybrid approach to brain extraction from premature infant MRI. In: SCIA 2011, Scandinavian Conference on Image Analysis, 23-27 May 2011, Ystad Saltsjobad, Sweden.

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Abstract

This paper describes a novel automatic skull-stripping method for premature infant data. A skull-stripping approach involves the removal of non-brain tissue from medical brain images. The new method reduces the image artefacts, generates binary masks and multiple thresholds, and extracts the region of interest. To define the outer boundary of the brain tissue, a binary mask is generated using morphological operators, followed by region growing and edge detection. For a better accuracy, a threshold for each slice in the volume is calculated using k-means clustering. The segmentation of the brain tissue is achieved by applying a region growing and finalized with a local edge refinement. This technique has been tested and compared to manually segmented data and to four well-established state of the art brain extraction methods.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:computer vision; Skull Stripping; Newborns MRI; Brain Segmentation
Subjects:UNSPECIFIED
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:18595
Deposited On:13 Aug 2013 13:07 by Mark Sweeney . Last Modified 11 Jan 2019 13:18

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