This paper describes effort towards automatic tissue segmentation in neonatal MRI. Extremely low contrast to noise ratio (CNR), regional intensity changes due to RF coil inhomogeneity and biology, and tissue property changes due to the early myelination and axon pruning processes require a methodology that combines the strength of spatial priors (template atlas), data modelling, and prior knowl...

Brain tissue segmentation of Magnetic Resonance Imaging (MRI) is an important and one of the challenging tasks in medical image processing. MRI images of brain are classified into two types: classifying tissues, anatomical structures. It comprised into different tissue classes which contain four major regions, namely Gray matter (GM), White matter (WM), Cerebrospinal fluid (CSF), and Background...

Automated brain tumor segmentation and detection are vastly important in medical diagnostics because it provides information related to anatomical structures as well as potential abnormal tissue necessary to delineate appropriate surgical planning. As the segmentation of anatomical regions of the brain is the fundamental problem in medical image analysis. Segmentation of Brain tumor appropriate...

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 chil...

Brain tissue segmentation is an important component of the clinical diagnosis brain diseases using multi-modal magnetic resonance imaging (MR). has been developed by many unsupervised methods in literature. The most commonly used are K-Means, Expectation-Maximization, and Fuzzy Clustering. clustering offer considerable benefits compared with aforementioned as they capable handling images that c...

White-matter hyperintensity (WMH) is a primary biomarker for small-vessel cerebrovascular disease, Alzheimer’s disease (AD), and others. The association of WMH with brain structural changes has also recently been reported. Although fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) provide valuable information about WMH, FLAIR does not other normal tissue information. ...

Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...

This thesis deals with the fully automatic generation of semantic annotations for medical imaging data by means of medical image segmentation and labeling. In particular, we focus on the segmentation of the human brain and related structures from magnetic resonance imaging (MRI) data. We present three novel probabilistic methods from the field of database-guided knowledge-based medical image se...