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Detection techniques for melanoma diagnosis: A performance evaluation

机译:黑色素瘤诊断检测技术:性能评估

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摘要

Melanoma which is most commonly spread skin cancer in United States, UK and Australia and it has been estimated that about 12,650 people died from this cancer in the year 2013 in UK. Thus, early detection and diagnosis of the tumor is most important. And according to survey it was found that 60% of claim lodged against Medical Protection Society for incorrect diagnosis by doctors or negligence of medical reports due to system failure. So, accurate diagnosis is required for effective treatment of melanoma. This paper presents various diagnostic techniques such as Menzies scale method, Seven Point checklist, Asymmetry, Border, Color, Diameter (ABCD)rule based method and Pattern Analysis method for early diagnosis of cancer. The methodology which is been followed in diagnosis of skin cancer is also presented and a comparative study of various edge detection, an image preprocessing and segmentation technique are proposed. In our study, analysis has been done on number of samples melanoma clinical images and it has been observed that Canny edge detection and preprocessing using Otsu method is the best approach. Due to importance of image segmentation a number of algorithm have been proposed and based on image that is inputted in the algorithm should be chosen to give the best results.
机译:黑色素瘤是在美国,英国和澳大利亚最普遍传播的皮肤癌,据估计,2013年在英国约有12650人死于该癌症。因此,早期发现和诊断肿瘤是最重要的。并且根据调查发现,有60%的索赔是针对医生的错误诊断或由于系统故障而导致的医疗报告疏忽而向医学保护协会提出的。因此,有效治疗黑素瘤需要准确的诊断。本文介绍了各种诊断技术,如孟氏量表法,七点检查表,不对称,边界,颜色,直径(ABCD)规则和模式分析法,可用于癌症的早期诊断。提出了在皮肤癌诊断中应遵循的方法,并对各种边缘检测,图像预处理和分割技术进行了比较研究。在我们的研究中,已经对许多样本的黑色素瘤临床图像进行了分析,并且已经观察到使用Otsu方法进行Canny边缘检测和预处理是最好的方法。由于图像分割的重要性,已经提出了许多算法,并且应该基于输入到算法中的图像来选择图像,以获得最佳效果。

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