1 research outputs found
Learning to Detect Blue-white Structures in Dermoscopy Images with Weak Supervision
We propose a novel approach to identify one of the most significant
dermoscopic criteria in the diagnosis of Cutaneous Melanoma: the Blue-whitish
structure. In this paper, we achieve this goal in a Multiple Instance Learning
framework using only image-level labels of whether the feature is present or
not. As the output, we predict the image classification label and as well
localize the feature in the image. Experiments are conducted on a challenging
dataset with results outperforming state-of-the-art. This study provides an
improvement on the scope of modelling for computerized image analysis of skin
lesions, in particular in that it puts forward a framework for identification
of dermoscopic local features from weakly-labelled data