01695nas a2200241   4500000000100000000000100001008004100002260001200043653001700055653001100072653002300083653001300106653001400119653001300133100002500146700001800171245005700189856009800246300001000344490000600354520107900360022001401439       2017                            d  c09/201710aSegmentation10aCancer10aFeature Extraction10aMedicine10aDiagnosis10aMelanoma1 aAbbas Hassin Alasadi1 aBaidaa Alsafy00aDiagnosis of Malignant Melanoma of Skin Cancer Types  uhttp://www.ijimai.org/journal/sites/default/files/files/2016/12/ijimai20174_5_8_pdf_89993.pdf  a44-490 v43 aMalignant melanoma is a kind of skin cancer that begins in melanocytes. It can influence on the skin only, or it may expand to the bones and organs. It is less common, but more serious and aggressive than other types of skin cancer. Malignant Melanoma can happen anywhere on the skin, but it is widespread in certain locations such as the legs in women, the back and chest in men, the face, the neck, mouth, eyes, and genitals. In this paper, a proposed algorithm is designed for diagnosing malignant melanoma types by using digital image processing techniques. The algorithm consists of four steps: preprocessing, separation, features extraction, and diagnosis. A neural network (NN) used to diagnosis malignant melanoma types. The total accuracy of the neural network was 100% for training and 93% for testing. The evaluation of the algorithm is done by using sensitivity, specificity, and accuracy. The sensitivity of NN in diagnosing malignant melanoma types was 95.6%, while the specificity was 92.2% and the accuracy was 93.9%. The experimental results are acceptable.  a1989-1660