https://hal.inria.fr/hal-02132147/document

New advances in the Clinica software platform for clinical neuroimaging studies

An MRI time course of 512 echo-planar images (EPI) in resting human brain obtained every 250 ms reveals fluctuations in signal intensity in each pixel that have a physiologic origin. Regions of the sensorimotor cortex that were activated secondary to hand movement were identified using functional MRI methodology (FMRI). Time courses of low frequency (< 0.1 Hz) fluctuations in resting brain were observed to have a high degree of temporal correlation (P < 10(-3)) within these regions and also with time courses in several other regions that can be associated with motor function. It is concluded that correlation of low frequency fluctuations, which may arise from fluctuations in blood oxygenation or flow, is a manifestation of functional connectivity of the brain.

Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.

https://cogns.northwestern.edu/cbmg/TBSSNI2006.pdf

Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.

In this paper the authors present a new approach for the nonrigid registration of contrast-enhanced breast MRI. A hierarchical transformation model of the motion of the breast has been developed. The global motion of the breast is modeled by an affine transformation while the local breast motion is described by a free-form deformation (FFD) based on B-splines. Normalized mutual information is used as a voxel-based similarity measure which is insensitive to intensity changes as a result of the contrast enhancement. Registration is achieved by minimizing a cost function, which represents a combination of the cost associated with the smoothness of the transformation and the cost associated with the image similarity. The algorithm has been applied to the fully automated registration of three-dimensional (3-D) breast MRI in volunteers and patients. In particular, the authors have compared the results of the proposed nonrigid registration algorithm to those obtained using rigid and affine registration techniques. The results clearly indicate that the nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.

/pdf/nonrigid-registration-using-free-form-deformations-2olitefstb.pdf

Nonrigid registration using free-form deformations: application to breast MR images

Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain.

PURPOSE: A new nonrigid registration method, designed to reduce the effect of movement artifact in subtraction images from breast MR, is compared with existing rigid and affine registration methods. METHOD: Nonrigid registration was compared with rigid and affine registration methods and unregistered images using 54 gadolinium-enhanced 3D breast MR data sets. Twenty-seven data sets had been previously reported normal, and 27 contained a histologically proven carcinoma. The comparison was based on visual assessment and ranking by two radiologists. RESULTS: When analyzed by two radiologists independently, all three registration methods gave better-quality subtraction images than unregistered images (p < 0.01), but nonrigid registration gave significantly better results than the rigid and affine registration methods (p < 0.01). There was no significant difference between rigid and affine registration methods. CONCLUSION: Nonrigid registration significantly reduces the effects of movement artifact in subtracted contrast-enhanced breast MRI. This may enable better visualization of small tumors and those within a glandular breast

Comparison and evaluation of rigid, affine, and nonrigid registration of breast MR images

Biomechanical models of the breast are being developed for a wide range of applications including image alignment tasks to improve diagnosis and therapy monitoring, imaging related studies of the biomechanical properties of lesions, and image guided interventions. In this paper we present a method to evaluate the accuracy with which biomechanical breast models based on finite element methods (FEM) can predict the displacements of tissue within the breast. Our experimental data was obtained by compressing the breast of a volunteer in a controlled manner, and the acquisition of MR images of the breast before and after compression. Non-rigid registration of these two MR volumes together with interactive identification of corresponding landmarks provided an independent estimate of the displacements. In addition, the non-rigid registration provided estimates of the displacements of the surface points (skin points) of the breast. The accuracy of the FEM models was evaluated using all or a subset of these surface displacements as boundary conditions. The influence of pectoral muscle movement on the performance of the FEM models was also investigated. Our initial results indicate that the accurate setting of the boundary conditions is more important than the actual choice of elastic properties in these compression scenarios. With the complete boundary conditions, the displacements agreed to within 2.6 mm for all FEM models on average. Assuming no movement at the posterior or the medial side of the breast, the accuracy of the FEM models deteriorated to worse than 4.6 mm for all models.

A method for the comparison of biomechanical breast models

We present initial results from evaluating the accuracy with which biomechanical breast models based on finite element methods can predict the displacements of tissue within the breast. We investigate the influence of different tissue elasticity values, Poisson's ratios, boundary conditions, finite element solvers and mesh resolutions on one data set. MR images were acquired before and after compressing a volunteer's breast gently. These images were aligned using a 3D non-rigid registration algorithm. The boundary conditions were derived from the result of the non-rigid registration or by assuming no patient motion at the deep or medial side. Three linear and two non-linear elastic material models were tested. The accuracy of the BBMs was assessed by the Euclidean distance of twelve corresponding anatomical landmarks. Overall, none of the tested material models was obviously superior to another regarding the set of investigated values. A major average error increase was noted for partially inaccurate boundary conditions at high Poisson's ratios due to introduced volume change. Maximal errors remained, however, high for low Poisson's ratio due to the landmarks closeness to the inaccurate boundary conditions. The choice of finite element solver or mesh resolution had almost no effect on the performance outcome.

Comparison of biomechanical breast models: a case study

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Papers

Nonrigid registration using free-form deformations: application to breast MR images

Comparison and evaluation of rigid, affine, and nonrigid registration of breast MR images

A method for the comparison of biomechanical breast models

Comparison of biomechanical breast models: a case study