Background and objective: To ensure proper functioning of a Computer Aided Diagnosis
(CAD) system for melanoma detection in dermoscopy images, it is important to accurately …

Automatic segmentation of skin lesions is the first step towards development of a computer-
aided diagnosis of melanoma. Although numerous segmentation methods have been …

This paper proposes a computer assisted diagnostic system for the detection of melanoma
in dermoscopy images. Clinical findings have concluded that in case of melanoma, the …

Background: Skin cancer is one of the most common forms of cancers among humans. It can
be classified as non-melanoma and melanoma. Although melanomas are less common than …

In this paper we propose a machine learning approach to classify melanocytic lesions as
malignant or benign, using dermoscopic images. The lesion features used in the …

Background Computer-aided segmentation and border detection in dermoscopic images is
one of the core components of diagnostic procedures and therapeutic interventions for skin …

We propose a deep learning approach to segment the skin lesion in dermoscopic images.
The proposed network architecture uses a pretrained EfficientNet model in the encoder and …

Developing automatic diagnostic tools for the early detection of skin cancer lesions in
dermoscopic images can help to reduce melanoma-induced mortality. Image segmentation …

Purpose Computerized prescreening of suspicious moles and lesions for malignancy is of
great importance for assessing the need and the priority of the removal surgery. Detection …

In this paper, we propose and evaluate six methods for the segmentation of skin lesions in
dermoscopic images. This set includes some state of the art techniques which have been …