Yazar "Yildiz, Mustafa Zahid" seçeneğine göre listele

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    Development of new descriptor for melanoma detection on dermoscopic images
    (Springer Heidelberg, 2020) Akan, Hasan; Yildiz, Mustafa Zahid
    Early detection of melanoma has critical importance for the success of the treatment. However, a successful early diagnosis is only possible with the existence of discriminative features. In this study, a new descriptor based on the number of colors was developed in order to successfully diagnose lesions of melanoma. The number of colors is the main feature in the identification of melanoma-type skin lesions. The user must select a threshold value when calculating the number of colors of the lesion. The incorrect threshold value selection of non-expert users disrupts the aforementioned feature and also leads to significant diagnostic errors. In this study, it was revealed that color counting threshold values have a significant effect on the distinctiveness of the number of colors. In the three dermoscopic databases, color counting threshold values that provide the maximum distinctiveness on melanoma and benign lesions were determined as 0 and 0.123 respectively. By using these color counting threshold values, the number of colors for each sample in the data sets was calculated separately. Following that, a novel attribute called the number of color difference was defined as a function of color counting threshold values. Experiments using only the proposed new descriptor yielded 52.7% higherf-measure and 84.5% higher true-positive performance than the number of colors used in the literature. The results obtained in this study revealed the importance of accurately determining the number of colors the lesions had and states that the applied color counting threshold significantly influences the classification results. Thereby, a new method is proposed for determining the critical color counting threshold. We claim that the classical ABCD rule should be improved by our new descriptor.
  • Küçük Resim
    Öğe
    Investigation of Color Difference in Diagnosis of Melanoma
    (Ieee, 2020) Akan, Hasan; Yildiz, Mustafa Zahid
    Skin cancer has become more common in recent years. Melanoma is the deadliest type of skin cancers. Early diagnosis increases the success of treatment in all types of cancer. The success of early diagnosis depends on the attributes used to identify the disease. Weak attributes require more complex classifiers and increase diagnostic error. Color features were an important indicator in the diagnosis of melanoma. The most important of these was the number of color, but no specific method has been proposed in the literature for its calculation. In this study, a method that provides the determination of the required threshold values to accurately calculate the number of colors of the lesions was proposed and a new attribute named color difference has been defined. For the threshold values determined in the proposed method and the threshold values in the literature, the color numbers and color difference attribute of all samples were calculated. Calculated attributes were analyzed statistically. The results of the analysis showed that the number of colors and color difference attribute calculated with the proposed method were significant. However, it was observed that the number of colors calculated with the threshold values used in the literature did not have statistical significance. Finally, univariate classification was made with the proposed color difference attribute and the number of colors calculated according to the methods in the literature. The classification results were compared in terms of f-measure and it was found that the color difference attribute was 25.8% to 31.9% more successful than the other number of colors used in the literature. The results obtained showed that the importance of correctly determining the number of colors of the lesions and the proposed color difference attribute were quite effective.