This document has been written to illustrate the role that assumptions play in the design of image analysis algorithms. We present several common methods for the segmentation of MR data on the basis of underlying tissue. These methods, which may appear disparate at first sight, are discussed and related in terms of the assumptions regarding the data fornmation process needed to derive them. We summarise the use of these techniques using a flow diagram which makes explicit the questions which need to be addressed in order that they are used appropriately
In this dissertation we present a new approach to estimate the volume of ischermic stroke lesions us...
Various physiological modelling studies require isolating the anatomy of interest from medical imag...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
This document has been written to illustrate the role that assumptions play in the design of image a...
<p>Image segmentation of white matter and grey matter using manual segmentation on a slice-by-slice ...
When attempting to segment data in an image, though we may be unaware of it, we are really asking a ...
Many papers are published every year containing new methodologies for brain tissue segmentation in m...
This thesis presents a computational framework and new algorithms for creating geometric models and ...
Magnetic Resonance (MR) imaging is a 3-D, multi-slice, radiological technique that acquires multiple...
Image segmentation aims to separate objects of interests from the background in an image. It has an ...
The presented method addresses the problem of multi-spectral image segmentation through use of a mod...
An algorithm was designed to discriminate tissue types, including pathology, utilizing 3D data sets ...
The problem of tumorous tissues segmentation of MR brain images: • Tumorous tissues vary in size, sh...
Analysis of medical images is resource demanding and time-consuming, and automatic procedures are ne...
Brain vessel segmentation is a fundamental component of cerebral disease screening systems. However,...
In this dissertation we present a new approach to estimate the volume of ischermic stroke lesions us...
Various physiological modelling studies require isolating the anatomy of interest from medical imag...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...
This document has been written to illustrate the role that assumptions play in the design of image a...
<p>Image segmentation of white matter and grey matter using manual segmentation on a slice-by-slice ...
When attempting to segment data in an image, though we may be unaware of it, we are really asking a ...
Many papers are published every year containing new methodologies for brain tissue segmentation in m...
This thesis presents a computational framework and new algorithms for creating geometric models and ...
Magnetic Resonance (MR) imaging is a 3-D, multi-slice, radiological technique that acquires multiple...
Image segmentation aims to separate objects of interests from the background in an image. It has an ...
The presented method addresses the problem of multi-spectral image segmentation through use of a mod...
An algorithm was designed to discriminate tissue types, including pathology, utilizing 3D data sets ...
The problem of tumorous tissues segmentation of MR brain images: • Tumorous tissues vary in size, sh...
Analysis of medical images is resource demanding and time-consuming, and automatic procedures are ne...
Brain vessel segmentation is a fundamental component of cerebral disease screening systems. However,...
In this dissertation we present a new approach to estimate the volume of ischermic stroke lesions us...
Various physiological modelling studies require isolating the anatomy of interest from medical imag...
121 p.Segmentation of MRI data is required for many applications, such as the comparison of differen...