Akademik Veri Yönetim Sistemi
Computers in Biology and Medicine, cilt.152, 2023 (SCI-Expanded)
© 2022 Elsevier LtdComputerized methods provide analyses of skin lesions from dermoscopy images automatically. However, the images acquired from dermoscopy devices are noisy and cause low accuracy in automated methods. Therefore, various methods have been applied for denoising in the literature. There are some review-type papers about these methods. However, their authors have focused on either denoising with a specific approach or denoising from other images rather than dermoscopy images, which have a different characteristic. It is not possible to determine which method is the most suitable for denoising from dermoscopy images according to the results presented in them. Therefore, a review on the denoising approaches applied with dermoscopy images is required and, according to our knowledge, there is no such a review-type paper. To fill this gap in the literature, the required review has been performed in this work. Also, in this work, the methods in the literature have been implemented using the same data sets containing images with speckle or Gaussian types of noise. The results have been analyzed not only visually but also quantitatively to compare capabilities of the techniques. Our experiments indicated that each denoising technique has its own disadvantages and advantages. The main contributions of this paper are three-fold: (i) A comprehensive review on the denoising approaches applied with dermoscopy images has been presented. (ii) The denoising techniques have been implemented with the same images for meaningful comparisons. (iii) Both visual and quantitative analyses with different metrics have been performed and comparative performance evaluations have been presented.