Biomedical Image Processing / Medical Image Processing
Hamid Abrishami Moghaddam; Maryam Momeni; Kamran Kazemi; Reinhard Grebe; Fabrice Wallois
Volume 4, Issue 4 , June 2010, , Pages 337-360
Abstract
Diagnostic follow-up of the brain development during the neonatal period and childhood is an important clinical task. Any disturbance of this process can cause pathological deviations, especially if the baby is born premature. Recent advances in magnetic resonance imaging allow obtaining high-resolution ...
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Diagnostic follow-up of the brain development during the neonatal period and childhood is an important clinical task. Any disturbance of this process can cause pathological deviations, especially if the baby is born premature. Recent advances in magnetic resonance imaging allow obtaining high-resolution images of the neonatal brain. After segmenting the brains they can be used to reconstruct and model changes occurring during neonatal brain development. In addition such near-realistic model of the head, including the skin, skull and brain can be used to solve the inverse problem of determining the sources of registered signals from electrical brain activity. Although there exist numerous methods and various modeling schemes for adults, these cannot be used directly for neonates due to important differences in morphology. In this review article, neonatal brain atlases are divided into three categories: individual atlases, probabilistic atlases and stochastic atlases. In the following, existing neonatal brain atlases are placed in this classification and their methods of construction are presented. Furthermore, strengths and weaknesses of those neonatal brain atlases are analyzed and finally future research trends in this area are explained.
