55 citations · 113 across the 5 of their papers we have counts for
5 papers
Cross-Sim-NGF: FFT-Based Global Rigid Multimodal Alignment of Image Volumes using Normalized Gradient Fields
Johan Öfverstedt, Joakim Lindblad, Nataša Sladoje
Multimodal image alignment involves finding spatial correspondences between volumes varying in appearance and structure. Automated alignment methods are often based on local optimi…
Fast computation of mutual information in the frequency domain with applications to global multimodal image alignment
Johan Öfverstedt, Joakim Lindblad, Nataša Sladoje
Multimodal image alignment is the process of finding spatial correspondences between images formed by different imaging techniques or under different conditions, to facilitate hete…
Is Image-to-Image Translation the Panacea for Multimodal Image Registration? A Comparative Study
Jiahao Lu, Johan Öfverstedt, Joakim Lindblad +1
Despite current advancement in the field of biomedical image processing, propelled by the deep learning revolution, multimodal image registration, due to its several challenges, is…
INSPIRE: Intensity and spatial information-based deformable image registration
Johan Öfverstedt, Joakim Lindblad, Nataša Sladoje
We present INSPIRE, a top-performing general-purpose method for deformable image registration. INSPIRE brings distance measures which combine intensity and spatial information into…
CoMIR: Contrastive Multimodal Image Representation for Registration
Nicolas Pielawski, Elisabeth Wetzer, Johan Öfverstedt +4
We propose contrastive coding to learn shared, dense image representations, referred to as CoMIRs (Contrastive Multimodal Image Representations). CoMIRs enable the registration of…