Paper
12 May 1995 Reproducibility study for volume estimation in MRI of the brain using the Eigenimage algorithm
Author Affiliations +
Abstract
Accurate and reproducible volume calculations are essential for diagnosis and treatment evaluation for many medical situations. Current techniques employ planimetric methods that are very time consuming to obtain reliable results. The reproducibility and accuracy of these methods depend on the user and the complexity of the volume being measured. We have reported on an algorithm for volume calculation that uses the Eigenimage filter to segment a desired feature from surrounding, interfering features. The pixel intensities of the resulting image have information pertaining to partial volume averaging effects in each voxel preserved thus providing an accurate volume calculation. Also, the amount of time required is significantly reduced, as compared to planimetric methods, and the reproducibility is less user dependent and is independent of the volume shape. In simulations and phantom studies the error in accuracy and reproducibility of this method were less than 2%. The purpose of this study was to determine the reproducibility of the method for volume calculations of the human brain. Ten volunteers were imaged and the volume of white matter, gray matter, and CSF were estimated. The time required to calculate the volume for all three tissues was approximately one minute per slice. The inter- and intra-observer reproducibility errors were less than 5% on average for all volumes calculated. These results were determined to be dependent on the proper selection of the ROIs used to define the tissue signature vectors and the non-uniformity of the MRI system.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joe P. Windham, Donald J. Peck, and Hamid Soltanian-Zadeh "Reproducibility study for volume estimation in MRI of the brain using the Eigenimage algorithm", Proc. SPIE 2434, Medical Imaging 1995: Image Processing, (12 May 1995); https://doi.org/10.1117/12.208720
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Cited by 1 scholarly publication.
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KEYWORDS
Tissues

Image segmentation

Brain

Image filtering

Magnetic resonance imaging

Image processing algorithms and systems

Image analysis

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