Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

Retinal illnesses such as diabetic retinopathy (DR) are the main causes of vision loss. In the
early recognition of eye diseases, the segmentation of blood vessels in retina images plays …

Accurate skin lesion segmentation in dermoscopic images is crucial to the early diagnosis of
skin cancers. However, it remains a challenging task due to fuzzy lesion boundaries …

Background: Automated intelligent systems for unbiased diagnosis are primary requirement
for the pigment lesion analysis. It has gained the attention of researchers in the last few …

The occurrence rates of melanoma are rising rapidly, which are resulting in higher death
rates. However, if the melanoma is diagnosed in Phase I, the survival rates increase. The …

Many modern neural network architectures with over parameterized regime have been used
for identification of skin cancer. Recent work showed that network, where the hidden units …

Malignant melanoma is the deadliest form of skin cancer and, in recent years, is rapidly
growing in terms of the incidence worldwide rate. The most effective approach to targeted …

In this paper, we present an architecture for classification of pigmented skin lesions from
dermatoscopic images. The architecture is using image preprocessing for natural hair …

Segmentation of skin lesions from dermoscopic images plays an essential role in the early
detection of skin cancer. However, skin lesion segmentation is still challenging due to …

Malignant melanoma is known as the deadliest type of skin cancer. Nowadays, several
automatic diagnosis systems have been developed in order to improve the detection of …