Frequency domain registration of computer tomography data

Abstract

This paper presents a new method for registering computer tomography (CT) volumetric data of human bone structures relative to observations made at different times. The system we advance was tested with different kinds of CT data sets. In this paper we report on some representative experimental results obtained with the CT data of the hip bones of a patient prior to and after prosthetic surgery aimed at the reconstruction of the hip articulation. The method works with rigid data having arbitrary relative position and orientation and proves to be robust with respect to CT acquisition noise and with respect to the segmentation technique adopted to select the region of interest for registration. The method is capable of registering correctly data sets taken from the same articulation and whose components have undergone small relative displacements. The method is also amenable to registration of heteregeneous kinds of volumetric data, e.g., CT scans and Magnetic Resonance Imagery (MRI) scans, which show different characteristics in correspondence to the same organic structure.

Invited Review—image Registration in Veterinary Radiation Oncology: Indications, Implications, and Future Advances

“…Rigid transformation methods are most commonly used and usually applied on images that have no distortion, such as CT to CT. Generally, a rigid geometric transformation can be achieved by translation and rotation and is commonly used to match between bones on medical images, such as the skull. 38,39 An affine transformation, which is an extension of the rigid transformation, allows for rotations, translations, scaling, and shearing. 40 Rigid transformations can also be applied before a nonrigid registration as an image conditioning step.…”

“…This describes the geometrical shift that is required for the target image to match it to the reference image. Rigid transformation methods are most commonly used and usually applied on images that have no distortion, such as CT to CT. Generally, a rigid geometric transformation can be achieved by translation and rotation and is commonly used to match between bones on medical images, such as the skull . An affine transformation, which is an extension of the rigid transformation, allows for rotations, translations, scaling, and shearing .…”

Computer Image Registration Techniques Applied to Nuclear Medicine Images

“…However, a higher number of parameters in the transformation model can introduce undesirable transformations and therefore, a regularization term must be taken into account [37][38][39]. Non-rigid image transformations can be achieved using basis functions such as a set of Fourier [40][41][42][43] or Wavelet basis functions [44]. Image registration using splines can be achieved with techniques based on the assumption that a set of control points are mapped into the target image from their corresponding counterparts in the source image [45], and a displacement field can be established and interpolated [46].…”

Spatiotemporal 3D image registration for mesoscale studies of brain development

“…Fourier transformations (Hughes, 1992) and wavelets (He et al, 1994) were used to identify independent image components, which were then registered separately. Feature-based registration techniques have proven to be efficient on low-resolution medical images (Andreetto et al, 2004).…”