Deep learning methods have achieved significant results in various fields. Due to the
success of these methods, many researchers have used deep learning algorithms in …

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease that results in a
progressive decline in cognitive abilities. Since AD starts several years before the onset of …

Discriminative learning, restorative learning, and adversarial learning have proven
beneficial for self-supervised learning schemes in computer vision and medical imaging …

Diffusion probabilistic models have been shown to generate state-of-the-art results on
several competitive image synthesis benchmarks but lack a low-dimensional, interpretable …

Low-Dose Computed Tomography (LDCT) technique, which reduces the radiation harm to
human bodies, is now attracting increasing interest in the medical imaging field. As the …

Dealing with missing modalities in Magnetic Resonance Imaging (MRI) and overcoming
their negative repercussions is considered a hurdle in biomedical imaging. The combination …

Multi-instance learning (MIL) is widely adop-ted for automatic whole slide image (WSI)
analysis and it usually consists of two stages, ie, instance feature extraction and feature …

Medical image acquisition plays a significant role in the diagnosis and management of
diseases. Magnetic Resonance (MR) and Computed Tomography (CT) are considered two …

Multimodal medical images have been widely applied in various clinical diagnoses and
treatments. Due to the practical restrictions, certain modalities may be hard to acquire …

Discriminative, restorative, and adversarial learning have proven beneficial for self-
supervised learning schemes in computer vision and medical imaging. Existing efforts …