Algorithm for brain extraction on magnetic resonance images T1 using morphological 3D transformations
Abstract
In this paper, a 3D morphological composition of transformations for brain extraction on brain Magnetic Resonance Images T1 (MRI T1) is presented. The proposal makes use of two morphological connected transformations, the lower leveling and a family of the viscous alternating sequential filters (VASFs). The properties of these operators -which consist in the control of the reconstruction process of a marker into the original image-, are exploited to segment the brain in 20 volumes of MRI T1. The segmented brains are compared with respect to: i) the segmentations obtained from BET which is popular among the scientific community for segmenting the brain; and ii) manual segmentations. The computed indices indicate that the proposed transformation produces good results during its performance. The consumed time for the algorithm during the execution is acceptable and it can be implemented in Matlab.
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