RATIONALE AND OBJECTIVES: This article deals with an automatic tissue segmentation of brain magnetic resonance imaging (MRI) in young children. MATERIALS AND METHODS: We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the brain MRI in young children. We develop a method of creation of a population-specific atlas in young children using a single manual segmentation. The method is based on nonlinear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. RESULTS: Using this approach, we significantly improve the performance of the popular expectation-maximization algorithm on brain MRI in young children. The method can be used for building probabilistic atlases with any number of structures. We compare resulting algorithm with nonrigid registration-based label propagation. CONCLUSIONS: Finally, both methods are used to measure the volume of seven brain structures and measure the growth between 1 and 2 years of age.
RATIONALE AND OBJECTIVES: This article deals with an automatic tissue segmentation of brain magnetic resonance imaging (MRI) in young children. MATERIALS AND METHODS: We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the brain MRI in young children. We develop a method of creation of a population-specific atlas in young children using a single manual segmentation. The method is based on nonlinear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. RESULTS: Using this approach, we significantly improve the performance of the popular expectation-maximization algorithm on brain MRI in young children. The method can be used for building probabilistic atlases with any number of structures. We compare resulting algorithm with nonrigid registration-based label propagation. CONCLUSIONS: Finally, both methods are used to measure the volume of seven brain structures and measure the growth between 1 and 2 years of age.
Authors: Laura Igual; Joan Carles Soliva; Antonio Hernández-Vela; Sergio Escalera; Xavier Jiménez; Oscar Vilarroya; Petia Radeva Journal: Biomed Eng Online Date: 2011-12-05 Impact factor: 2.819
Authors: Piotr A Habas; Kio Kim; Francois Rousseau; Orit A Glenn; A James Barkovich; Colin Studholme Journal: Med Image Comput Comput Assist Interv Date: 2008
Authors: Katyucia de Macedo Rodrigues; Emma Ben-Avi; Danielle D Sliva; Myong-Sun Choe; Marie Drottar; Ruopeng Wang; Bruce Fischl; Patricia E Grant; Lilla Zöllei Journal: Front Hum Neurosci Date: 2015-02-18 Impact factor: 3.169
Authors: Piotr A Habas; Kio Kim; Francois Rousseau; Orit A Glenn; A James Barkovich; Colin Studholme Journal: Med Image Comput Comput Assist Interv Date: 2009