There is an ongoing debate on how to model diffusivity in fiber crossings. We propose an optimization framework for the selection of a dual tensor model and the set of diffusion weighting parameters, such that both the diffusion shape and orientation parameters can be precisely as well as accurately estimated. For that, we have adopted the Cramer-Rao lower bound (CRLB) on the variance of the model parameters, and performed Monte Carlo simulations. We have found that the axial diffusion lambda(vertical bar vertical bar) needs to be constrained, while an isotropic fraction can be modeled by a single parameter f(iso). Under these circumstances, the Fractional Anisotropy (FA) of both tensors can theoretically be independently estimated with a precision of 9% (at SNR = 25). Levenberg-Marquardt optimization of the Maximum Likelihood function with a Rician noise model approached this precision while the bias was insignificant. A two-element b-vector b = [10.0 3.5]. 10(3) mm(-2)s was found to be sufficient for estimating parameters of heterogeneous tissue with low error. This has allowed us to estimate consistent FA-profiles along crossing tracts. This work defines fundamental limits for comparative studies to correctly analyze crossing white matter structures.

Diagnosing of injuries of the wrist bones is problematic due to a highly complex and variable geometry. knowledge of variations of healthy bone shapes is essential to detect wrist pathologies, developing prosthetics and investigating biomechanical properties of the wrist joint. In previous literature various methods have been proposed to classify different scaphoid and lunate types. These classifications were mainly qualitative or were based on a limited number of manually determined surface points. The purposes of this study are to develop a quantitative, standardized description of the variations in the scaphoid and lunate and to investigate whether it is feasible to divide carpal bones in isolated shape categories based on statistical grounds. The shape variations of the scaphoid and lunate were described by constructing a statistical shape model (SSM) of healthy bones. SSM shape parameters were determined that describe the deviation of each shape from the mean shape. The first five modes of variation in the SSMs describe 60% of the total variance of the scaphoid and 57% of the lunate. Higher modes describe less than 5% of the variance per mode. The distributions of the parameters that characterize the bone shape variations along the modes do not significantly differ from a normal distribution. The SSM provides a description of possible shape variations and the distribution of scaphoid and lunate shapes in our population at an accuracy of approximately the voxel size (0.3x0.3x0.3mm(3)). The developed statistical shape model represents the previously qualitatively described variations of scaphoid and lunate. However, strict classifications based on shape differences are not feasible on statistical grounds.

The feasibility of air-coupled ultrasound transducers to detect laser-induced ultrasound from artificial blood vessels embedded in an optically scattering phantom is demonstrated. These air-coupled transducers allow new applications in biomedical photoacoustic imaging where contact with tissue is not preferred. One promising application of such transducers is the addition of photoacoustic imaging to the regular x-ray mammographic screening procedure.

Measuring the diffusion properties of crossing fibers is very challenging due to the high number of model parameters involved and the intrinsically low SNR of Diffusion Weighted MR Images. Noise filtering aims at suppressing the noise while pertaining the data distribution. We propose an adaptive version of the Linear Minimum Mean Square Error (LMMSE) estimator to achieve this. Our filter applies an adaptive filtering kernel that is based on a space-variant estimate of the noise level and a weight consisting of the product of a Gaussian kernel and the diffusion similarity with respect to the central voxel. The experiments show that the data distribution after filtering is still Rician and that the diffusivity values are estimated with a higher precision while pertaining an equal accuracy. We demonstrate on brain data that our adaptive approach performs better than the initial LMMSE estimator.

The design of most ulnar head implants is currently not based on studies of anatomical variations. To enable prosthesis design based on anatomical features, a method is developed for the detection of the ulna surface that articulates with the radius head. The articulating surface is detected by combining partial articulating ulna surfaces detected in CT scans of different individuals in different poses. Correspondences between ulnae of different individuals are established through the construction of a statistical shape model (SSM) of the ulna head. The articulating surface is attached to this SSM, allowing the detection of articulating surfaces in ulnae that are not in the training set of the model. As a simple shape is desirable for prosthesis design, three quadratic surfaces were fitted to the articulating surfaces of 40 ulnae. The mean fitting error for the simplest surface, a cylinder, was 0.20 mm. As this error is smaller than the voxel size of 0.3 mm isotropic, it was concluded that the articulating ulna surface can be satisfactory approximated by a cylinder part.

Comparing wrist shapes of different individuals requires alignment of these wrists into the same pose. Unconstrained registration of the carpal bones results in anatomically nonfeasible wrists. In this paper, we propose to constrain the registration using the shapes of adjacent bones, by keeping the width of the gap between adjacent bones constant. The registration is formulated as an optimization involving two terms. One term aligns the wrist bones by minimizing the distances between corresponding bone surfaces. The second term constrains the registration by minimizing the distances between adjacent sliding surfaces. The registration is based on the Iterative Closest Point algorithm. All bones are registered concurrently so that no bias is introduced towards any of the bones. The proposed registration method delivers anatomically correct configurations of the bones. The registration errors are in the order of the voxel size of the acquired CT data (0.3 x 0.3 x 0.3 mm(3)). The standard deviation in the widths of gaps between adjacent bones is in the order of 10% with an insignificant bias. This is a large improvement over the standard deviations of 30%-80% encountered in unconstrained registration. The value of this method is its capability of accurately registering joints in varying poses resulting in physiological joint configurations.

We propose a novel technique for tract-based comparison of DTI-indices between groups, based on a representation that is estimated while matching fiber tracts. The method involves a non-rigid registration based on a joint clustering and matching approach, after which a 3D-atlas of cluster center points is used as a frame of reference for statistics. Patient and control FA-distributions are compared per cluster. Spatial consistency is taken to reflect a significant difference between groups. Accordingly, a non-parametric classification is performed to assess the continuity of pathology over larger tract regions. In a study to infant survivors treated for medulloblastoma with intravenous methotrexate and cranial radiotherapy, significant decreases in FA in major parts of the corpus callosum were found.

In Diffusion Tensor Imaging (DTI), differently oriented fiber bundles inside one voxel are incorrectly modeled by a single tensor. High Angular Resolution Diffusion Imaging (HARDI) aims at using more complex models, such as a two-tensor model, for estimating two fiber bundles. We propose a new method for creating experimental phantom data of fiber crossings, by mixing the DWI-signals from high FA-regions with different orientation. The properties of these experimental phantoms approach the conditions of real data. These phantoms can thus serve as a 'ground truth' in validating crossing reconstruction algorithms. The angular resolution of a dual tensor model is determined using series of crossings, generated under different angles. An angular resolution of 0.6π was found in data scanned with a diffusion weighting parameter b =1000 s/mm 2 . This resolution did not change significantly in experiments with b =3000 and 5000 s/mm 2 , keeping the scanning time constant.

In order to extend the clinical use of body surface mapping, we developed an efficient lead system which can be used under intensive care circumstances. The array consists of flexible straps with electrodes which are sucked onto the thorax by running pressurized air through venturi ejectors. Major features are: rapid application and removal, high reliability, easy handling, and suitability for repeated use with minimal discomfort to the patient.