Title :
Automatic segmentation of neonatal brain magnetic resonance images
Author :
Devi, Chelli N. ; Chandrasekharan, Anupama ; Sundararaman, V.K. ; Alex, Zachariah C.
Author_Institution :
Vellore Inst. of Technol., Vellore, India
Abstract :
This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.
Keywords :
biomedical MRI; brain; image segmentation; medical image processing; neurophysiology; paediatrics; probability; atlas-based probabilistic segmentations; automatic segmentation; morphology-based brain segmentation; myelinated portions; neonatal brain image segmentation; neonatal brain magnetic resonance images; Brain modeling; Image segmentation; Indexes; Magnetic resonance imaging; Manuals; Pathology; Pediatrics; Automatic segmentation; Brain atlas; Myelination; Neonatal brain magnetic resonance images;
Conference_Titel :
Communications and Signal Processing (ICCSP), 2014 International Conference on
Conference_Location :
Melmaruvathur
Print_ISBN :
978-1-4799-3357-0
DOI :
10.1109/ICCSP.2014.6949920