Automatic localization of skin lesions within dermoscopy images is a crucial step toward
developing a decision support system for skin cancer detection. However, segmentation of
the lesion image can be challenging, as these images possess various artifacts distorting
the uniformity of the lesion area. Recently, deep convolution learning-based techniques
have drawn great attention for pixel-wise image segmentation. These deep networks
produce coarse segmentation, and convolutional filters and pooling layers result in …

A dermoscopic lesion area is identified by: Obtaining a dermoscopic image and running a
convolutional neural network image classifier on the dermoscopic image to obtain pixelwise
lesion prediction scores. Segmenting the dermo scopic image into super-pixels, and
computing for each super-pixel an average of the pixelwise prediction scores for pixels
within that super-pixel. Computing a mean prediction score across the plurality of super-
pixels. Assigning a con fidence indicator of “1” to each super-pixel with a prediction score …