Morphometric analysis of white matter lesions in MR images: method and validation

The analysis of MR images is evolving from qualitative to quantitative. More and more, the question asked by clinicians is how much and where, rather than a simple statement on the presence or absence of abnormalities. The authors present a study in which the results obtained with a semiautomatic, m...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on medical imaging 1994-12, Vol.13 (4), p.716-724
Main Authors: Zijdenbos, A.P., Dawant, B.M., Margolin, R.A., Palmer, A.C.
Format: Article
Language:English
Subjects:
Anisotropic magnetoresistance
Area measurement
Artificial neural networks
Biological and medical sciences
Filtering algorithms
Humans
Image analysis
Image segmentation
Investigative techniques, diagnostic techniques (general aspects)
Lesions
Manuals
Medical sciences
Nervous system
Radiodiagnosis. Nmr imagery. Nmr spectrometry
Statistics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The analysis of MR images is evolving from qualitative to quantitative. More and more, the question asked by clinicians is how much and where, rather than a simple statement on the presence or absence of abnormalities. The authors present a study in which the results obtained with a semiautomatic, multispectral segmentation technique are quantitatively compared to manually delineated regions. The core of the semiautomatic image analysis system is a supervised artificial neural network classifier augmented with dedicated preand postprocessing algorithms, including anisotropic noise filtering and a surface-fitting method for the correction of spatial intensity variations. The study was focused on the quantitation of white matter lesions in the human brain. A total of 36 images from six brain volumes was analyzed twice by each of two operators, under supervision of a neuroradiologist. Both the intra- and interrater variability of the methods were studied in terms of the average tissue area detected per slice, the correlation coefficients between area measurements, and a measure of similarity derived from the kappa statistic. The results indicate that, compared to a manual method, the use of the semiautomatic technique not only facilitates the analysis of the images, but also has similar or lower intra- and interrater variabilities.< >
ISSN:0278-0062
1558-254X
DOI:10.1109/42.363096