Pathology Artificial Intelligence Platform (PAIP) is a free research platform in support of
pathological artificial intelligence (AI). The main goal of the platform is to construct a high-quality …

Nonrigid image registration is an important task for many medical imaging applications. In
particular, for radiation oncology it is desirable to track respiratory motion for thoracic cancer …

Respiratory and cardiac motion is the most serious limitation to whole-body PET, resulting
in spatial resolution close to 1 cm. Furthermore, motion-induced inconsistencies in the …

Recently developed deep-learning-based denoisers often outperform state-of-the-art
conventional denoisers, such as the BM3D. They are typically trained to minimizethe mean …

Deep image prior (DIP) serves as a good inductive bias for diverse inverse problems. Among
them, denoising is known to be particularly challenging for the DIP due to noise fitting with …

Blind non-uniform image deblurring for severe blurs induced by large motions is still
challenging. Multi-scale (MS) approach has been widely used for deblurring that sequentially …

Often, labeling large amount of data is challenging due to high labeling cost limiting the
application domain of deep learning techniques. Active learning (AL) tackles this by querying the …

Rotation invariance has been an important topic in computer vision tasks. Ideally, robot
grasp detection should be rotation-invariant. However, rotation-invariance in robotic grasp …

Image super-resolution is a common task on mobile and IoT devices, where one often
needs to upscale and enhance low-resolution images and video frames. While numerous …

Recent 3D generative models have achieved remarkable performance in synthesizing high
resolution photorealistic images with view consistency and detailed 3D shapes, but training …