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-white structure (BWS). In this paper, we achieve this goal in a multiple instance learning (MIL) framework using only image-level labels indicating whether the feature is present or not. To this aim, each image is represented as a bag of (nonoverlapping) regions, where each region may or may not be identified as an instance of BWS.

Multi-Instance Classification by Max-Margin Training of Cardinality-Based Markov Networks.

We propose a probabilistic graphical framework for multi-instance learning (MIL) based on Markov networks. This framework can deal with different levels of labeling ambiguity (i.e.