In previous research, a watershed-based algorithm was shown to be useful for automatic
lesion segmentation in dermoscopy images, and was tested on a set of 100 benign and …

Background/purpose: Automatic lesion segmentation is an important part of computer‐
based image analysis of pigmented skin lesions. In this research, a watershed algorithm is …

Background/purpose: Automated border detection is an important and challenging task in
the computerized analysis of dermoscopy images. However, dermoscopic images often …

Purpose We present a classifier for automatically selecting a lesion border for dermoscopy
skin lesion images, to aid in computer‐aided diagnosis of melanoma. Variation in …

In a computerized image analysis environment, the irregularity of a lesion border has been
used to differentiate between malignant melanoma and other pigmented skin lesions. The …

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 …

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 …

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 …

The skin cancer was analyzed by dermoscopy helpful for dermatologists. The classification
of melanoma and carcinoma such as basal cell, squamous cell, and merkel cell carcinomas …

Accurate skin lesion segmentation is important for identification and classification through
computational methods. However, when performed by dermatologists, the results of clinical …