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 …

Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

Manual diagnosis of skin cancer is time-consuming and expensive; therefore, it is essential
to develop automated diagnostics methods with the ability to classify multiclass skin lesions …

Dermoscopy images can be classified more accurately if skin lesions or nodules are
segmented. Because of their fuzzy borders, irregular boundaries, inter-and intra-class …

Melanoma skin cancer is considered as one of the most common diseases in the world.
Detecting such diseases at early stage is important to saving lives. During medical …

Skin cancer is one of the most threatening diseases worldwide. However, diagnosing skin
cancer correctly is challenging. Recently, deep learning algorithms have emerged to …

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 …

As a popular probabilistic generative model, generative adversarial network (GAN) has
been successfully used not only in natural image processing, but also in medical image …

Skin lesion segmentation is a primary step for skin lesion analysis, which can benefit the
subsequent classification task. It is a challenging task since the boundaries of pigment …

Automatic tumor segmentation in breast ultrasound (BUS) images is still a challenging task
because of many sources of uncertainty, such as speckle noise, very low signal-to-noise …