Proposes a segmentation method for a quantitative image diagnosis as a means of realizing an objective diagnosis of the frontal lobe atrophy. From the data obtained on the grade of membership, the fractal dimensions of the cerebral tissue [cerebral spinal fluid (CSF), gray matter, and white matter] and the contours are estimated. The mutual relationship between the degree of atrophy and the fractal dimension has been analyzed based on the estimated fractal dimensions. Using a sample of 42 male and female cases, ranging In age from 50's to 70's, it has been concluded that the frontal lobe atrophy can be quantified by regarding it as an expansion of CSF region on the magnetic resonance imaging (MRI) of the brain. Furthermore, when the process of frontal lobe atrophy is separated into early and advanced stages, the volumetric change of CSF and white matter in frontal lobe displays meaningful differences between the two stages, demonstrating that the fractal dimension of CSF rises with the progress of atrophy. Moreover, an interpolation method for three-dimensional (3-D) shape reconstruction of the region of diagnostic interest is proposed and 3-D shape visualization, with respect to the degree and form of atrophy, is performed on the basis of the estimated fractal dimension of the segmented cerebral tissue.
[1]
Benoit B. Mandelbrot,et al.
Fractal Geometry of Nature
,
1984
.
[2]
R. Schmidt,et al.
Nuclear magnetic resonance image white matter lesions and risk factors for stroke in normal individuals.
,
1988,
Stroke.
[3]
Mohan Trivedi,et al.
Segmentation of a Thematic Mapper Image Using the Fuzzy c-Means Clusterng Algorthm
,
1986,
IEEE Transactions on Geoscience and Remote Sensing.
[4]
U Tiede,et al.
3-D segmentation of MR images of the head for 3-D display.
,
1990,
IEEE transactions on medical imaging.
[5]
Jeffrey J. Rodriguez,et al.
Edge-based segmentation of 3-D magnetic resonance images
,
1994,
Proceedings of 1st International Conference on Image Processing.
[6]
L M Fletcher,et al.
A multispectral analysis of brain tissues
,
1993,
Magnetic resonance in medicine.