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Detecting Cancer Cells of Mammographic Images Based on Top-Hat Transformation | ||
| Al-Mustansiriyah Journal of Science | ||
| Article 1, Volume 26, Issue 1, 2015, Pages 84-91 | ||
| Author | ||
| Layla Hussein | ||
| Abstract | ||
| Mammography breast cancer images assist detecting disease caused by cells normal growth and have the ability physicians .Software use to analyze these images may also use for assist physicians in their daily Mathematical Morphology is a theory which provides a number of useful tools for image analysis. In our proposed approach the Top-Hat transform is used to extract cancer cells from Mammography breast cancer images. Top-Hat transformation operated in morphology which is used for extracting small or narrow, bright or dark features in an image. This paper have been proposed an approach to extract cancer cells by using Top-Hat filtering with circular structuring element with different diameter (10, 20, 30, 40, and 50) . This approach applies on three different mammography cancer images with properties. Image 1 Type: JPEG Image Size: 556200 bytes Class: unit 8 Dimension: 618px*300px x3. Image 2 Type: JPEG Image Size: 283500 bytes Class: unit 8 Dimensions: 350px * 270 px x33- image 3 Type: JPEG Image Size: 359976 bytes Class: unit 8 Dimensions: 424px * 283 px x3. The experimental results show how the different in circular structuring element are affected extracting the cancer cells of images. And we applied some post-processing after top-hat filtering by using an adaptive mask to enhance the resultant images. | ||
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