Fuzzy object growth model for neonatal brain MR understanding

Abstract

This chapter summaries a brain region segmentation method for newborn using magnetic resonance (MR) images. The method deploys fuzzy object growth model (FOGM) which is an extension of fuzzy object model. It is a 4-dimensional model which gives a prior knowledge of brain shape and position at any growing time. First we calculate 4th dimension of FOGM, called growth index in this chapter. Because the growth index will be different from person to person even in the same age group, the method estimates the growth index from cerebral shape using Manifold learning. Using the growth index, FOGM is constructed from the training dataset. To recognize the brain region in evaluating subject, it first estimates the growth index. Then, the brain region is segmented using fuzzy connected image segmentation with the FOGM matched by the growth index. To evaluate the method, this study segments the parenchymal region of 16 subjects (revised age; 0–2 years old) using synthesized FOGM.