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Development and Validation of Techniques for Brain Morphometry

Objective

BIOMORPH is a project to develop improved techniques for measurement of the size and shape of biological structures (morphometry). Morphometry has become increasingly important since the advent of non-invasive magnetic resonance imaging which is providing large volumes of data from normal as well as abnormal individuals in vivo and allows time changes to be studied.

The techniques to be developed are generic, but the project is focused on schizophrenia and multiple sclerosis, applications in neurology and psychiatry where the need for improved morphometric techniques is particularly clear. These are common diseases of great economic and social as well as medical importance. Even small advances in management could lead to substantial savings. In schizophrenia, changes in the morphology of various brain structures are thought to provide important clues to the most fundamental brain abnormalities that underlie the condition, but the changes are barely detectable with current techniques and more research is needed to confirm and extend existing data. In multiple sclerosis, quantification of changes in lesions has become of great importance for pharmaceutical trials, and improved morphometry would reduce the cost of developing new drugs.

The basic requirements for improved morphometry are similar in the different applications. Measurement of size is hampered by the difficulties of detecting and localising the boundaries of structures in images (segmentation), particularly in three dimensions, but there have been recent advances in segmentation which could now strengthen morphometric studies. Experts regularly describe normal and abnormal shape in the language of anatomy and medicine but developing and validating computational techniques has proved difficult. In the BIOMORPH project, we will develop and validate improved techniques for measurement of size. shape and challenges over time of brain structures shown on MR images in schizophrenia and multiple sclerosis. The clinical research collaborators are active in clinical research and will be able to take immediate advantage of technological advances that arise through the project. They will be supported by strong computer vision groups who will undertake the computational work.

During the first phase of the project MR images will be segmented interactively by the clinical experts and simple morphometry carried out. The anatomical objects thus formed will then be studied by the experts and traditional (mainly linguistic) shape descriptors applied to them. Computer shaped descriptors will also be applied and will be added to the data base of objects and their attributes. This sequence will be repeated in the second phase US advanced computer tools developed earlier in the project. Finally, these data will be analysed to establish the differences in size and shape measurements within the group of experts, within normal subjects, within patients suffering from one of the clinical disorders, and between normals and each clinical category. The of the computer methods will then be evaluated by comparing them with the expert methods in their reproducibility and their ability to segregate normal from abnormal subjects.

Funding Scheme

CSC - Cost-sharing contracts

Coordinator

University of Kent at Canterbury
Address

CT2 7NT Canterbury
United Kingdom

Participants (4)

Eidgenössische Technische Hochschule
Switzerland
Address
35,Gloriastrasse
8092 Zürich
Institut National de Recherches en Informatique et en Automatique
France
Address
2004,Route Des Lucioles
06561 Valbonne - Sophia Antipolis
Katholieke Universiteit Leuven
Belgium
Address
54,Kardinaal Mercierlaan 54
3001 Heverlee
The Chancellor, Master and Scholars of the University of Oxford
United Kingdom
Address

OX3 7JX Oxford