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 …

Recent works on plug-and-play image restoration have shown that a denoiser can implicitly
serve as the image prior for model-based methods to solve many inverse problems. Such a …

A common shortfall of supervised deep learning for medical imaging is the lack of labeled
data, which is often expensive and time consuming to collect. This article presents a new …

We propose a novel transformer model, capable of segmenting medical images of varying
modalities. Challenges posed by the fine-grained nature of medical image analysis mean …

Inspired by the great success of deep neural networks (DNNs), many unfolding methods
have been proposed to integrate traditional image modeling techniques, such as dictionary …

Automatic skin lesion analysis of dermoscopy images remains a challenging topic. In this
paper, we propose an end-to-end multi-task deep learning framework for automatic skin …

Skin biopsy histopathological analysis is one of the primary methods used for pathologists to
assess the presence and deterioration of melanoma in clinical. A comprehensive and …

In this paper, we propose particle swarm optimization (PSO)-enhanced ensemble deep
neural networks and hybrid clustering models for skin lesion segmentation. A PSO variant is …

This paper reviews the NTIRE 2019 challenge on real image denoising with focus on the
proposed methods and their results. The challenge has two tracks for quantitatively …