Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …

This paper presents a review of automated image registration methodologies that have been
used in the medical field. The aim of this paper is to be an introduction to the field, provide …

This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver
registration for image-pairs works by patch-wise prediction of a deformation model based …

Deep learning algorithms are powerful tools for analyzing, restoring and transforming
bioimaging data. One promise of deep learning is parameter-free one-click image analysis …

3D medical image registration is of great clinical importance. However, supervised learning
methods require a large amount of accurately annotated corresponding control points (or …

Publicly available scientific resources help establish evaluation standards, provide a
platform for teaching and improve reproducibility. Version 4 of the Insight ToolKit (ITK4) …

The United States National Institutes of Health (NIH) commit significant support to open-
source data and software resources in order to foment reproducibility in the biomedical …

Deformable registration of images obtained from different modalities remains a challenging
task in medical image analysis. This paper addresses this important problem and proposes …

One of the most challenging problems in modern neuroimaging is detailed characterization
of neurodegeneration. Quantifying spatial and longitudinal atrophy patterns is an important …

We propose an efficient non-parametric diffeomorphic image registration algorithm based on
Thirion's demons algorithm. In the first part of this paper, we show that Thirion's demons …