With the improvement of hardware computing power and the development of deep learning
algorithms, a revolution of" artificial intelligence (AI)+ medical image" is taking place …

Medical imaging methods, such as CT scans, MRI scans, X-rays, and ultrasound imaging,
are widely used for diagnosis in the healthcare domain. However, these methods are often …

Recent advances in deep learning have been pushing image denoising techniques to a
new level. In self-supervised image denoising, blind-spot network (BSN) is one of the most …

In recent years, the development of deep learning has been pushing image denoising to a
new level. Among them, self-supervised denoising is increasingly popular because it does …

Recently a number of studies demonstrated impressive performance on diverse vision-
language multi-modal tasks such as image captioning and visual question answering by …

This paper reviews the first challenge on high-dynamic range (HDR) imaging that was part
of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in …

Prostate cancer is one of the most identified cancers and second most prevalent among
cancer-related deaths of men worldwide. Early diagnosis and treatment are substantial to …

Image denoising is the key component in several computer vision and image processing
operations due to unavoidable noise in the image generation process. For medical image …

Deep learning based solutions are being succesfully implemented for a wide variety of
applications. Most notably, clinical use-cases have gained an increased interest and have …

Medical image acquisition devices are susceptible to producing blurry images due to
respiratory and patient movement. Despite having a notable impact on such blind-motion …