Showing papers in "Medical Image Analysis in 2001"

TL;DR: It is demonstrated that the use of local optimisation methods together with the standard multi-resolution approach is not sufficient to reliably find the global minimum, so a global optimisation method is proposed that is specifically tailored to this form of registration.

TL;DR: Magnetic resonance elastography shows promise as a potential technique for 'palpation by imaging', with possible applications in tumor detection, characterization of disease, and assessment of rehabilitation (particularly in muscle).

TL;DR: An early review of the largely unknown territory of human-computer interaction in image segmentation is presented to identify patterns in the use of interaction and to develop qualitative criteria to evaluate interactive segmentation methods.

TL;DR: The problem of automatic segmentation of complicated curvilinear structures in three-dimensional imagery, with the primary application of segmenting vasculature in magnetic resonance angiography (MRA) images, is addressed.

TL;DR: In this paper, the authors proposed a more automatic path tracking method for virtual endoscopy inside 3D medical images, which is based on previous work by Cohen and Kimmel [Int. J. Comp. Vis. 24 (1) (1997) 57] for extracting paths in 2D images using Fast Marching algorithm.

TL;DR: An evaluation of convolution-based interpolation methods and rigid transformations for the specific task of applying geometrical transformations to medical images shows that spline interpolation is to be preferred over all other methods, both for its accuracy and its relatively low computational cost.

TL;DR: It was found that an exponential stress-strain law could accurately fit uniform stress test data and that subsequent finite element modelling for non-uniform stress around a small indentor matched measured force characteristics.

TL;DR: A methodology for estimating cardiac deformations from 3D echocardiography (3DE) that shows good agreement with previously published results in the literature and exhibits a high correlation with strains produced in the same animals using implanted sonomicrometers.

TL;DR: A spatial/symbolic model of the inner organs is developed, which is based on more than 1000 cryosections and congruent fresh and frozen CT images of the male Visible Human, offering an unsurpassed photorealistic presentation and level of detail.

TL;DR: A method to infer the connectivity induced by white matter fibers in the living human brain by inferring a regularized direction map from diffusion data and a study of the tracking behavior according to the weight given to the regularization is proposed.

TL;DR: This paper presents a strategy for the segmentation of brain from volumetric MR images which integrates 3D segmentation and 3D registration processes, using an automatic registration method to initialize the surface, as an alternative solution to manual initialization.

TL;DR: The tracking process is also successfully applied to 3D contrast enhanced MR digital subtracted angiography (3D-CE-MRA) of the inferior member vessels, and detection of artery stenosis for routine clinical use is possible due to the high precision of the tracking algorithm.

TL;DR: The methods permit creation of detailed vascular trees from segmented 3D image data and provide examples of clinically useful visualizations enabled by the methodology and taken from a visualization program now in clinical use.

TL;DR: An exploratory data-driven strategy based on Unsupervised Fuzzy Clustering Analysis and its potential for fMRI data analysis in the temporal domain is presented and an original validity criterion is proposed taking into account data geometry and the partition Membership Functions.

TL;DR: It is advocated the viewpoint that the aperture and the 3D interpolation problem may be solved simultaneously by finding the simplest displacement field, obtained by a geometry-constrained diffusion, which in a precise sense yields the simplest displacements field.

TL;DR: The usefulness of the system developed, based on this method, is analyzed for human brain mapping and neuroradiology, and is a step forward in bringing the atlas and the clinical data together within a practical and powerful solution that is fast and flexible, yet low-cost and affordable.

TL;DR: The results show that FADS is able to extract factor curves correlated to arterial and venous signal intensity curves and that the corresponding factor images allow a distinction to be made between areas of the brain with normal and abnormal perfusion.

TL;DR: This paper focuses on the automatic labeling of the left coronary tree in X-ray angiography, based on a 3D topological model built from the 3D anthropomorphic phantom, Coronix, and demonstrates successful scores of 90% correct labeling for the main arteries and 60% for the sub-branches.

TL;DR: A novel non-rigid registration method is proposed for registration of the Talairach-Tournoux brain atlas with MRI images and the Schaltenbrand-WahrenBrain atlas that not only matches the model to the data efficiently, but also decreases the degrees of freedom of the system and consequently reduces the computational cost.

TL;DR: This paper describes how sequential freehand 3D ultrasound, which does not employ an interpolated voxel array, can be used to measure the volume of large organs.

TL;DR: A series of 3D statistical models of the cortical sulci are presented, built from points located automatically over the sulcal fissures, and corresponded automatically using variants on the iterative closest point algorithm.

TL;DR: A mathematical model for studying the passive kinematics of total knee prostheses can be useful in computer-aided planning and guidance of total joint replacement and the design of new prosthetic joints.

TL;DR: By incorporating knowledge about lead geometric and material properties, the 3-D finite element/active contour method regularizes the image reconstruction problem and allows for more quantitative and automatic assessment of implanted lead mechanics.

TL;DR: An evaluation of using one such tool, called the scale-space primal sketch, for brain activation analysis, finds that the global approach with absolute base level has a higher degree of correspondence to a traditional statistical method than a local approach with relative base level.