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Detection of malignant Cases by Segmentation of Cells in Medical Images and Applying Fuzzy Logic Technique | ||
| JOURNAL OF THI-QAR SCIENCE | ||
| Article 1, Volume 4, Issue 4, 2014, Pages 71-74 | ||
| Authors | ||
| Salim J. Attia; Ziad M. Abood; Ibrahim R. Agool | ||
| Abstract | ||
| The process of detection and segmentation of cells is considered in digital optical images of human breast tissue as important base to diagnose the diseases. The major features of malignancy are related with the cells. It is therefore essential to operate a segmentation of the image, to isolate the cells from the rest of image, i. e., from other tissue components, and from some other undesirable elements of images. The recognition process includes a segmentation algorithm based on an adaptive imaging threshold procedure that is sensitive to local ranges in pixel intensity (minimum-maximum values). The statistical features are extracted from the images of cells like median, mode, mean and standard deviation. Then the fuzzy logic method is applied to detect breast cancer. | ||
| Keywords | ||
| Segmentation; adaptive threshold; optical imaging; Fuzzy logic | ||
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