Many existing image registration methods have difficulties in accurately describing significant rotation and bending of entities (e.g. organs) between two datasets. A common problem in this case is to ensure that the resulting registration is physically plausible, i.e. that the registration describes the actual bending/rotation occurring rather than just introducing expansion in some areas and ...

PURPOSE Due to lack of soft-tissue contrast, target distortion for the upper-abdomen targets such as pancreatic tumors is complicated and requiring sufficient remedy. By applying automatic contour propagation, the authors use the information obtained from 4D CT to test if the deformable image registration compensates the respiration-induced distortion of pancreatic tumor in free breathing (FB) ...

Purpose Deformable registration is now routinely used at many radiation oncology centers not only for automatic contouring, but also for diagnostic image registration and dose accumulation. In these applications, it is essential that these registrations are not only characterized with phantom studies, but also be checked on a per-patient basis around the regions where the deformable registratio...

Deformable medical image registration plays an important role in clinical diagnosis and treatment. Recently, the deep learning (DL) based methods have been widely investigated showed excellent performance computational speed. However, these cannot provide enough accuracy because of insufficient ability representing both global local features moving fixed images. To address this issue, paper has...

Optical coherence tomography (OCT) of the macula has become increasingly important in the investigation of retinal pathology. However, deformable image registration, which is used for aligning subjects for pairwise comparisons, population averaging, and atlas label transfer, has not been well-developed and demonstrated on OCT images. In this paper, we present a deformable image registration app...