Skin cancer is common nowadays. Early diagnosis of skin essential to increase patients’ survival rate. In addition traditional methods, computer-aided used in cancer. One the benefits this method that it eliminates human error diagnosis. images may contain noise such as like hair, ink spots, rulers, etc., lesion. For reason, removal required. The reduction lesion can be referred removal. This p...

Dermoskopi görüntüleme, deri kanseri teşhisi için dermotolojistler tarafından yaygın bir biçimde kullanılan tanı metodudur. Dermotolojik değerlendirmenin uzman kişiye bağlı, zaman alıcı ve sübjektif olmasından dolayı otomatik sistemler karar verme süreçlerine katkı sağlamaları tercih edilmektedir. Deri lezyon görüntülerinden melanomların tespit edilmesi hastalığın erken ile tedavi sürecini hızl...

This abstract describes the segmentation system used to participate in the challenge ISIC 2017: Skin Lesion Analysis Towards Melanoma Detection. Several preprocessing techniques have been tested for three color representations (RGB, YCbCr and HSV) of 392 images. Results have been used to choose the better preprocessing for each channel. In each case a neural network is trained to predict the Ja...

Skin diseases represent a variety of disorders that can affect the skin. In fact, early diagnosis plays central role in treatment this type disease. This scholarly article introduces novel approach to classifying skin by leveraging two ensemble learning techniques, encompassing multi-modal and multi-task methodologies. The proposed classifier integrates diverse information sources, including le...

Background: Skin cancer can quickly become fatal. An examination and biopsy of dermoscopic pictures are required to determine if skin is malignant or benign. However, these examinations be costly. Objective: In this research, we proposed deep learning (DL)-based approach identify a melanoma, the most dangerous kind cancer. DL particularly excellent in traits predicting requires vast number imag...

Due to its increasing incidence, skin cancer, and especially melanoma, is considered a major public health issue. Manually detecting lesions (SL) from dermoscopy images difficult time-consuming process. Thus, researchers designed computer-aided diagnosis (CAD) systems assist dermatologists in the early detection of cancer. Moreover, SL naturally exhibits long-tailed distribution due complex pat...