Deep learning technologies have dramatically reshaped the field of medical image
registration over the past decade. The initial developments, such as regression-based and U …

In content‐based image retrieval (CBIR), primitive image signatures are critical because
they represent the visual characteristics. Image signatures, which are algorithmically …

Medical image registration is vital for disease diagnosis and treatment with its ability to
merge diverse information of images, which may be captured under different times, angles …

Dense image prediction tasks demand features with strong category information and precise
spatial boundary details at high resolution. To achieve this, modern hierarchical models …

This paper introduces a novel top-down representation approach for deformable image
registration which estimates the deformation field by capturing various short-and long-range …

Neuroimage processing tasks like segmentation, reconstruction, and registration are central
to the study of neuroscience. Robust deep learning strategies and architectures used to …

Establishing voxelwise semantic correspondence across distinct imaging modalities is a
foundational yet formidable computer vision task. Current multi-modality registration …

Generative modeling has seen significant advancements in recent years, especially in the
realm of text-to-image synthesis. Despite this progress, the medical field has yet to fully …

Image registration and fusion are challenging tasks needed in manufacturing, including in
high-quality steel production for inspection, monitoring and safe operations. To solve some …

Recently, the revival of the semantic similarity concept has been featured by the rapidly
growing artificial intelligence research fueled by advanced deep learning architectures …