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CLASSIFICATION OF DIGITAL IMAGES USING CUMULATIVE INTERSECTION AND GENETIC ALGORITHM | ||
| AL-TAQANI | ||
| Article 1, Volume 25, Issue 1, 2012, Pages 0-0 | ||
| Authors | ||
| Seham ahamed; Maha Abdul Amir Kadhum | ||
| Abstract | ||
| A novel approach has been presented to detect and classify multiple sclerosis lesions in magnetic resonance images by using the cumulative Intersection method estimating the local fractal dimension for these images and allowing to distinguish between different types of brain tissues with respect to the human perception of roughness and statistical step - similarity of the under lying structure the offset of the Cumulative Intersection method in combination with the dimension are able to detect and distinguish lesions from other tissues by design the program Visual Basic V.6 . Also design the program to enhancement the images after reading the fractal dimension by using the genetic algorithm for resolution and high accuracy. | ||
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