MR image-based measurement of rates of change in volumes of brain structures. Part 1: Method and validation
Data(s) |
01/01/2002
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Resumo |
A detailed analysis procedure is described for evaluating rates of volumetric change in brain structures based on structural magnetic resonance (MR) images. In this procedure, a series of image processing tools have been employed to address the problems encountered in measuring rates of change based on structural MR images. These tools include an algorithm for intensity non-uniforniity correction, a robust algorithm for three-dimensional image registration with sub-voxel precision and an algorithm for brain tissue segmentation. However, a unique feature in the procedure is the use of a fractional volume model that has been developed to provide a quantitative measure for the partial volume effect. With this model, the fractional constituent tissue volumes are evaluated for voxels at the tissue boundary that manifest partial volume effect, thus allowing tissue boundaries be defined at a sub-voxel level and in an automated fashion. Validation studies are presented on key algorithms including segmentation and registration. An overall assessment of the method is provided through the evaluation of the rates of brain atrophy in a group of normal elderly subjects for which the rate of brain atrophy due to normal aging is predictably small. An application of the method is given in Part 11 where the rates of brain atrophy in various brain regions are studied in relation to normal aging and Alzheimer's disease. (C) 2002 Elsevier Science Inc. All rights reserved. |
Identificador | |
Idioma(s) |
eng |
Publicador |
Elsevier Science Inc |
Palavras-Chave | #Radiology, Nuclear Medicine & Medical Imaging #Structural Magnetic Resonance Imaging #Rate Of Volumetric Change #Rate Of Brain Atrophy #Partial Volume Effect #Normal Aging #Magnetic-resonance Images #Tissue Classification #Intensity Nonuniformity #Automatic Correction #Alzheimers-disease #White-matter #Segmentation #Atrophy #Serial #Registration #C1 #291599 Biomedical Engineering not elsewhere classified #730305 Diagnostic methods |
Tipo |
Journal Article |