access icon free Multimodal non-rigid registration methods based on local variability measures in computed tomography and magnetic resonance brain images

This paper presents a novel non-rigid multimodal registration method that relies on three basic steps: first, an initial approximation of the deformation field is obtained by a parametric registration technique based on particle filtering; second, an intensity mapping based on local variability measures (LVM) is applied over the two images in order to overcome the multimodal restriction between them; and third, an optical flow method is used in an iterative way to find the remaining displacements of the deformation field. Hence the new methodology offers a solution for multimodal NRR by a quadratic optimisation over a convex surface, which allows independent motion of each pixel, in contrast to methods that parameterise the deformation space. To evaluate the proposed method, a set of magnetic resonance/computed tomography clinical studies (pre- and post-radiotherapy treatment) of three patients with cerebral tumour deformations of the brain structures was employed. The resulting registration was evaluated both qualitatively and quantitatively by standard indices of correspondence over anatomical structures of interest in radiotherapy (brain, tumour and cerebral ventricles). These results showed that one of the proposed LVM (entropy) offers a superior performance in estimating the non-rigid deformation field.

Inspec keywords: image registration; particle filtering (numerical methods); approximation theory; medical image processing; computerised tomography; brain; biomedical MRI

Other keywords: parametric registration technique; medical imaging; particle filtering; initial approximation; LVM; quadratic optimisation; tumour ventricles; multimodal nonrigid registration methods; deformation space; intensity mapping; radiotherapy; multimodal images; magnetic resonance-computed tomography; deformation field; brain ventricles; diagnostic procedures; magnetic resonance brain images; NRR; local variability measurement; anatomical structures; cerebral ventricles; convex surface; therapeutic procedures; computed tomography

Subjects: Interpolation and function approximation (numerical analysis); Numerical approximation and analysis; Computer vision and image processing techniques; Computerised instrumentation; Medical magnetic resonance imaging and spectroscopy; Biology and medical computing; Filtering methods in signal processing; X-ray techniques: radiography and computed tomography (biomedical imaging/measurement); Biomedical magnetic resonance imaging and spectroscopy; X-rays and particle beams (medical uses); Interpolation and function approximation (numerical analysis); Patient diagnostic methods and instrumentation

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