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Biomedical subjects

J L Prince

Publications and source records attributed to J L Prince.

6 recordsLinked to original sources
PubMed1998

Cardiac material markers from tagged MR images.

Tagged magnetic resonance imaging (MRI) has shown great promise in non-invasive analysis of heart motion. To replace implanted markers as a gold standard, however, tagged MRI must be able to track a sparse set of material points, so-called material markers, with high accuracy. This paper presents a new method for generating accurate motion estimates over a sparse set of material points using standard, parallel-tagged MR images. Each tracked point is located at the intersection of three tag surfaces, each of which is estimated using a thin-plate spline. The intersections are determined by an iterative alternating projections algorithm for which a proof of convergence is provided. The resulting data sets are compatible with applications developed to exploit implanted marker data. One set of these material markers from a normal human volunteer is examined in detail using several methods to visualize the markers. Numerical results that include additional studies are also discussed. Finally, an error analysis is presented using a computer-simulated left ventricle for which material markers are tracked with an RMS error of approximately 0.2 mm for typical imaging parameters and noise levels.

Algorithms↗
PubMed1995

Optimization of MR pulse sequences for Bayesian image segmentation.

A method for optimizing MR imaging pulse sequence parameters in a statistical framework is presented. Parameters are defined to be optimal when the resulting scalar images yield optimal image segmentations using Bayesian pixel classification. Thus, Bayes risk is used as the objective function to minimize. Approximations are made to give a tractable solution in a four-step procedure. A sample calculation is carried out to determine the optimal TR and flip angle for scalar SPGR imaging of the brain. Overall, this paper gives a new approach to optimize MRI pulse sequences for the specific objective of improved image segmentation.

Bayes Theorem↗
PubMed1992

Measurement of radiotracer concentration in brain gray matter using positron emission tomography: MRI-based correction for partial volume effects.

Accuracy in in vivo quantitation of brain function with positron emission tomography (PET) has often been limited by partial volume effects. This limitation becomes prominent in studies of aging and degenerative brain diseases where partial volume effects vary with different degrees of atrophy. The present study describes how the actual gray matter (GM) tracer concentration can be estimated using an algorithm that relates the regional fraction of GM to partial volume effects. The regional fraction of GM was determined by magnetic resonance imaging (MRI). The procedure is designated as GM PET. In computer simulations and phantom studies, the GM PET algorithm permitted a 100% recovery of the actual tracer concentration in neocortical GM and hippocampus, irrespective of the GM volume. GM PET was applied in a test case of temporal lobe epilepsy revealing an increase in radiotracer activity in GM that was undetected in the PET image before correction for partial volume effects. In computer simulations, errors in the segmentation of GM and errors in registration of PET and MRI images resulted in less than 15% inaccuracy in the GM PET image. In conclusion, GM PET permits accurate determination of the actual radiotracer concentration in human brain GM in vivo. The method differentiates whether a change in the apparent radiotracer concentration reflects solely an alteration in GM volume or rather a change in radiotracer concentration per unit volume of GM.

Algorithms↗
PubMedDate not supplied

A computerized approach for morphological analysis of the corpus callosum.

OBJECTIVE: A new technique for analyzing the morphology of the corpus callosum is presented, and it is applied to a group of elderly subjects. MATERIALS AND METHODS: The proposed approach normalizes subject data into the Talairach space using an elastic deformation transformation. The properties of this transformation are used as a quantitative description of the callosal shape with respect to the Talairach atlas, which is treated as a standard. In particular, a deformation function measures the enlargement/shrinkage associated with this elastic deformation. Intersubject comparisons are made by comparing deformation functions. RESULTS: This technique was applied to eight male and eight female subjects. Based on the average deformation functions of each group, the posterior region of the female corpus callosum was found to be larger than its corresponding region in the males. The average callosal shape of each group was also found, demonstrating visually the callosal shape differences between the two groups in this sample. CONCLUSION: The proposed methodology utilizes the full resolution of the data, rather than relying on global descriptions such as area measurements. The application of this methodology to an elderly group indicated sex-related differences in the callosal shape and size.

Aged↗