Multimodal image matching, which refers to identifying and then corresponding the same or
similar structure/content from two or more images that are of significant modalities or …

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 the last decade, convolutional neural networks (ConvNets) have been a major focus of
research in medical image analysis. However, the performances of ConvNets may be limited …

The establishment of image correspondence through robust image registration is critical to
many clinical tasks such as image fusion, organ atlas creation, and tumor growth monitoring …

Abstract Knowledge of whole heart anatomy is a prerequisite for many clinical applications.
Whole heart segmentation (WHS), which delineates substructures of the heart, can be very …

The alignment of images through deformable image registration is vital to clinical
applications (eg, atlas creation, image fusion, and tumor targeting in image-guided …

Establishing dense anatomical correspondence across distinct imaging modalities is a
foundational yet challenging procedure for numerous medical image analysis studies and …

Abstract Domain Adaptation (DA) has recently been of strong interest in the medical imaging
community. While a large variety of DA techniques have been proposed for image …

In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion
segmentation challenge providing training and test data to registered participants. The …

During the last decades, the research community of medical imaging has witnessed
continuous advances in image registration methods, which pushed the limits of the state-of …