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Biomedical subjects

Mark Jenkinson

Publications and source records attributed to Mark Jenkinson.

23 records · Page 2Linked to original sources
PubMed2002

Optimization of static field homogeneity in human brain using diamagnetic passive shims.

These preliminary studies demonstrate that static field inhomogeneity in the human inferior frontal cortex (IFC) is significantly diminished through placement of a small amount of strongly diamagnetic material in the roof of the mouth. As a result, susceptibility-related image artifacts in this region, as observed in blood oxygen level dependent (BOLD) functional MRI (fMRI), are considerably decreased without compromising the spatial or temporal resolution of the study. Simulations of the static field utilizing perturbation theory are shown, which support the experimental results. The limitations and possible future developments of the technique are described. The application of diamagnetic passive shimming on other regions of the brain is also discussed. Routine use of the proposed method within fMRI studies is practicable through subject-specific optimization of the technique utilizing the simulation algorithm.

Brain↗
PubMed2002

Accurate, robust, and automated longitudinal and cross-sectional brain change analysis.

Quantitative measurement of brain size, shape, and temporal change (for example, in order to estimate atrophy) is increasingly important in biomedical image analysis applications. New methods of structural analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method of longitudinal (temporal change) analysis, SIENA, was presented previously. In this paper, improvements to this method are described, and also an extension of SIENA to a new method for cross-sectional (single time point) analysis. The methods are fully automated, robust, and accurate: 0.15% brain volume change error (longitudinal): 0.5-1% brain volume accuracy for single-time point (cross-sectional). A particular advantage is the relative insensitivity to differences in scanning parameters. The methods provide easy manual review of their output by the automatic production of summary images which show the results of the brain extraction, registration, tissue segmentation, and final atrophy estimation.

Algorithms↗
PubMed2002

Improved optimization for the robust and accurate linear registration and motion correction of brain images.

Linear registration and motion correction are important components of structural and functional brain image analysis. Most modern methods optimize some intensity-based cost function to determine the best registration. To date, little attention has been focused on the optimization method itself, even though the success of most registration methods hinges on the quality of this optimization. This paper examines the optimization process in detail and demonstrates that the commonly used multiresolution local optimization methods can, and do, get trapped in local minima. To address this problem, two approaches are taken: (1) to apodize the cost function and (2) to employ a novel hybrid global-local optimization method. This new optimization method is specifically designed for registering whole brain images. It substantially reduces the likelihood of producing misregistrations due to being trapped by local minima. The increased robustness of the method, compared to other commonly used methods, is demonstrated by a consistency test. In addition, the accuracy of the registration is demonstrated by a series of experiments with motion correction. These motion correction experiments also investigate how the results are affected by different cost functions and interpolation methods.

Acoustic Stimulation↗
PubMed2002

Fast, fully automated global and local magnetic field optimization for fMRI of the human brain.

The aim of this novel technique is to allow researchers, particularly those operating at high static magnetic field strengths on fMRI applications, to tailor the static magnetic field within the brain. The optimum solution for their experimental needs is reached, utilizing the full potential of the active shims at their disposal. The method for shimming human brain, which incorporates automatic brain segmentation to remove nonbrain tissue from the optimization routine, is presented and validated. The technique is fast, robust, and accurate, achieving the global minimum to a static field homogeneity function of the in vivo brain. Both global and specified local regions of the brain can be selected on which to optimize the shims without requiring skilled intervention. The effectiveness of the automated local shim is demonstrated in an olfactory fMRI study where significant activations in the orbitofrontal cortex were very clear when the above method was employed.

Adult↗