We present an extension of the symmetric ICP algorithm that is unbiased for an arbitrary number (N > or = 2) of shapes, using rigid transformations and scaling. The method does not require the selection of a reference shape or registration order and hence it is unbiased towards any of the registered shapes. The functional to be minimized is non-linear in the transformation parameters and thus c...

We present a fast, interactive local rigid registration application to localize tumour’s position for radiotherapy. The aim of the application is to automatically localize in a therapy CT dataset the target volume marked in a plan CT before applying a therapy. The algorithm is fast because it restricts the registration to a small area of the whole dataset. Once the target is found, the applicat...

This paper introduces a fast non-rigid registration method for aligning pre-operative 1.5 T MR images to intra-operative 0.5 T MR images for guidance in prostate biopsy. After the acquisition of both pre-operative 1.5 T and intra-operative 0.5 T, an intensity correction method is applied to the pre-operative images to reduce the significant artifacts in the signal intensities due to the presenc...

BACKGROUND Subtraction of Dynamic Contrast-Enhanced 3D Magnetic Resonance (DCE-MR) volumes can result in images that depict and accurately characterize a variety of liver lesions. However, the diagnostic utility of subtraction images depends on the extent of co-registration between non-enhanced and enhanced volumes. Movement of liver structures during acquisition must be corrected prior to subt...

BACKGROUND Registering CTs for patients receiving external beam radiotherapy (EBRT) with a boost dose from high-dose-rate brachytherapy (HDR) can be challenging due to considerable image discrepancies (e.g. rectal fillings, HDR needles, HDR artefacts and HDR rectal packing materials). This study is the first to comparatively evaluate image processing and registration methods used to register th...

We present 3D point-cloud registration techniques suited for scenarios where robustness to outliers and missing regions is necessary, besides being applicable both rigid non-rigid configurations. Our exploit advantages from deep learning models dense point matching recent advances in probabilistic modeling of registration. Such a combination produces context awareness resilience information. de...

Non-rigid registration has traditionally used physical models like elasticity and uids. These models are very seldom valid models of the di erence between the registered images. This paper presents a non-rigid registration algorithm, which uses a model of bone growth as a model of the change between time sequence images of the human mandible. By being able to register the images, this paper at ...

In many medical applications images are taken using techniques like x-ray Computed Tomography (CT) or Magnetic Resonance Imagining (MRI). For a wide range of applications two images, that have been taken from different perspectives, at different times, with different techniques or even from different individuals, have to be registered, so that corresponding features can be related. Although rig...

3D non-rigid registration is fundamental for tracking or reconstruction of 3D deformable shapes. Fast methods for 3D non-rigid registration are particularly interesting for markerless augmented reality applications, in which the object being used as a natural marker may undergo a non-rigid user interaction. Here, we present a multi-frame adaptive algorithm for 3D non-rigid registration implemen...

We describe in this paper a novel kind of geometrical transformations, named polyrigid and polyaffine. These transformations efficiently code for locally rigid or affine deformations with a small number of intuitive parameters. They can describe compactly large rigid or affine movements, unlike most free-form deformation classes. Very flexible, this tool can be readily adapted to a large variet...