Abstrakt

Breast cancer detection using image enhancement and segmentation algorithms

Yousif MY Abdallah, Sami Elgak, Hosam Zain, Mohammed Rafiq, Elabbas A. Ebaid, Alaeldein A. Elnaema

Enhancement of mammography images considers as powerful methods in categorization of breast normal tissues and pathologies. The digital image software gives chance to improve the mammographs and increasing their illustration value. The image processing methods in this paper were using contrast improvement, noise lessening, texture scrutiny and portioning algorithm. The mammography images kept in high quality to conserve the quality. Those methods aim to augment and hone the image intensity and eliminate noise from the images. The assortment factor of augmentation depends on the backdrop tissues and type of the breast lesions; hence, some lesions gave better improvement than the rest due to their density. The computation speed examined used correspondence and matching ratio. The results were 96.3 ± 8.5 (p>0.05). The results showed that the breast lesions could be improved by using the proposed image improvement and segmentation methods.