Showing papers in "Medical Image Analysis in 2003"

TL;DR: A novel, fully automatic, adaptive, robust procedure for brain tissue classification from 3D magnetic resonance head images (MRI) that customizes a training set, by using a 'pruning' strategy, such that the classification is robust against anatomical variability and pathology.

TL;DR: Weighted combinations of inversions from such directionally separated data sets can significantly improve reconstructions of shear modulus and attenuation in dynamic magnetic resonance elastography.

TL;DR: A multi-modal free-form registration algorithm based on maximization of mutual information for atlas-based brain tissue segmentation in MR images in case of gross morphological differences between atlas and patient images is proposed.

TL;DR: A novel curve evolution approach expressed in a level-set framework to achieve image intensity morphing and a simple non-linear PDE for the corresponding coordinate registration and atlas based segmentation of hippocampal shape from several MR brain scans is depicted.

TL;DR: A novel approach that incorporates the variability of an object population into the generation of a characteristic 3D shape model is described, a coarse-scale sampled medial description derived from a fine-scale spherical harmonics (SPHARM) boundary description.

TL;DR: The models fit the morphologies of the patients, and that the predicted soft tissue modifications are coherent with what they would expect, seems compatible with clinical use.

TL;DR: This study develops a physical standard to validate real-time soft tissue deformation models by taking CT images of a cube of silicone rubber with a pattern of embedded Teflon spheres that underwent uniaxial compression and spherical indentation tests.

TL;DR: The key observation is that multiple images may be segmented by evolving a single contour as well as the mappings of that contour into each image.

TL;DR: A multi-scale level set framework for segmentation of endocardial boundaries at each frame in a multiframe echocardiographic image sequence is presented and it is pointed out that the intensity distribution of an ultrasound image at a very coarse scale can be approximately modeled by Gaussian.

TL;DR: A novel segmentation technique, the histogram-based adaptive local thresholding (HALT), which extracts the useful information from an image without being affected by the presence of other structures, is developed, which indicates that the proposed drusen detector gives reliable detection accuracy in both position and mass size.

TL;DR: A generic volumetric biomechanical model from different image modalities and segmenting time series of medical images using this model can play an important role in the extraction of useful quantitative local parameters of cardiac function.

TL;DR: An automated system for registering computed tomography images of the chest temporally using an attenuation-based template matching approach that computes the optimal rigid-body transformation that aligns the corresponding landmarks in two CT scans of the same patient, and improves the processing time of the original ICP algorithm.

TL;DR: In a clinical study the parametric maps used by a clinician to detect the presence of malignant melanoma in a set of 348 pigmented lesions imaged using a commercial device, the SIAscope showed 80.1% sensitivity and 82.7% specificity in melanoma detection.

TL;DR: The in vivo investigation of joint kinematics in normal and injured wrist requires the segmentation of carpal bones from 3D images, and their registration over time is investigated, and a model which combines several approaches in a unified framework is proposed.

TL;DR: A generic automatic approach for the parcellation of the cortical surface into labeled gyri defined from a set of pairs of sulci selected by the user, illustrated with 12 different hemispheres.

TL;DR: A new algorithm for measuring the structure irregularities in the border is designed, which captured the knowledge of expert dermatologists in analysing malignancy of a lesion based on its shape alone, indicating that the new measures may be useful for diagnosing melanomas.

TL;DR: It is shown that more accurate and robust results may be obtained through seeking a joint solution to these linked processes through applying Markov random fields in the solution of a maximum a posteriori model of segmentation and registration.

TL;DR: The design, implementation and results of a unified non-rigid feature registration method for the purposes of anatomical MRI brain registration, which effectively reduces the computational complexity without sacrificing accuracy is described.

TL;DR: A novel statistical model is presented to estimate the in vivo material properties and strain and stress distribution in both ventricles, using data from noninvasive tagged magnetic resonance imaging and noticeable differences were found for normal volunteers and RVH patients.

TL;DR: A statistically robust, surface-based registration algorithm that has been used clinically in computer-integrated surgery for high tibial osteotomy, distal radius osteotom, and excision of osteoid osteoma is described.

TL;DR: In this article, the feasibility of cine magnetic resonance imaging (MRI) for assessment of the infarcted rat and mouse heart and to compare the results with established methods was evaluated.

TL;DR: A clinical overview of the results of a technique to transform the coordinates of regions of interest (ROIs) from the 2D mammograms to the spatial reference frame of the contrast-enhanced MRI volume.

TL;DR: It is shown through synthetic data that a probabilistic joint estimation strategy is needed to achieve more robust and accurate analysis of the kinematic functions and material parameters at the same time to achieve converged estimates because of the periodic nature of the cardiac dynamics.

TL;DR: It is shown that even though the motion of the C-arm is more precisely recovered using the navigation system, the projection geometry is better estimated using the attached CCD camera.

TL;DR: This paper investigates the feasibility and limitations of boundary detection in echocardiographic images based on the RF signal, introduces two types of RF-derived parameters: spectral autoregressive parameters and velocity-based parameters, and proposes a discontinuity adaptive framework to perform the detection task.

TL;DR: A new approach is presented for the assessment of a 3-D anatomical and functional model of the heart including structural information from magnetic resonance imaging (MRI) and functional information from positron emission tomography (PET) and magnetocardiography (MCG).

TL;DR: A framework that registers images with their reflections across the mid-sagittal plane, which accounts for tissue displacement through large deformation image warping and an efficient multi-scale algorithm for the joint estimation of structural and radiometric asymmetry is developed.

TL;DR: With upcoming new high-resolution magnetic resonance imaging (MRI) protocols, it appears worthwhile to examine the feasibility of characterizing the neocortical fine-structure from anatomical MRI scans, thus, defining neocorticals fields by in vivo techniques.

TL;DR: A novel framework for the segmentation, 3D reconstruction and web distribution of vessel structures specifically tailored to the assessment of abdominal aortic aneurysms for endovascular surgery planning is presented.

TL;DR: A probabilistic network model over image spaces and its broad utility in mammographic image analysis is demonstrated, particularly with respect to computer-aided diagnosis and qualitative assessment of model structure through mammographic synthesis.