Accurate localization of cortical convolutions in MR brain images

Analysis of brain images often requires accurate localization of cortical convolutions. Although magnetic resonance (MR) brain images offer sufficient resolution for identifying convolutions in theory, the nature of tomographic imaging prevents clear definition of convolutions in individual slices. Existing methods for solving this problem rely on heuristic adaptation of brain atlases created from a small number of individuals. These methods do not usually provide high accuracy because of large biological variations among individuals. The authors propose to localize convolutions by linking realistic visualizations of the cortical surface with the original image volume. They have developed a system so that a user can quickly localize key convolutions in several visualizations of an entire brain surface. Because of the links between the visualizations and the original volume, these convolutions are simultaneously localized in the original image slices. In the process of the authors' development, they have implemented a fast and easy method for visualizing cortical surfaces in MR images, thereby making their scheme usable in practical applications.     

Optimal image sampling schedule: a new effective way to reduce dynamic image storage space and functional image processing time

An optimal image sampling schedule for tracer dynamic studies with positron emission tomography (PET) is proposed. This schedule incorporates the characteristics of PET measurement and uses a new cost function and the D-optimal criterion. A detailed case study of the estimation of the local cerebral metabolic rate of glucose (LCMRGLc) using the tracer fluorodeoxyglucose (FDG) and the four-parameter FDG model is presented. As the sampling schedule designed requires only four dynamic images, the storage space and data processing time are greatly reduced, while the precision of the parameter estimates is almost the same as that achieved with a commonly used schedule. The effects of intersubject and intrasubject parameter variations on parameter estimation with the use of this optimal sampling schedule are investigated by computer simulation. The simulation results show that the estimation of parameters is sufficiently robust with respect to these intersubject and intrasubject variations. The optimal sampling schedule is quite suitable therefore for PET regional parameter estimation, as well as for image-wide parameter estimation, for different subjects.     

Characterization of Nonbonded Poly(ethylene oxide) Coating for Capillary Electrophoresis via Continuous Monitoring of Electroosmotic Flow

We examined changes in a poly(ethylene oxide) (PEO) coating by continuously monitoring the electroosmotic flow (EOF) in a fused-silica capillary during electrophoresis. An imaging CCD camera was used to follow the motion of a fluorescent neutral marker zone along the length of the capillary. The PEO coating was shown to reduce the velocity of EOF by more than 1 order of magnitude compared to a bare capillary at pH 7.0. However, it did not reduce EOF efficiently at pH 8.2. The coating protocol was important, especially at an intermediate pH of 7.7. Capillary reconditioning with an acidified solution of PEO was necessary in order to create a stable and efficient coating. In all cases we observed a gradual increase of EOF during extended runs, suggesting that the coating is slowly being degraded. The increase of pH in the cathodic (detection-end) buffer reservoir beyond pH ～8.0, e.g., as a result of electrolysis, had a large impact on the stability of the coating. This phenomenon may be used for the efficient and fast regeneration of the column surface and provides a simpler and more reliable alternative to pressure flushing of the capillary.     

Bayesian fused classification of medical images

In many applications in computer vision and signal processing, it is necessary to assimilate data from multiple sources. This is a particularly important issue in medical imaging, where information on a patient may be available from a number of different modalities. As a result, there has been much recent research interest in this area. The authors suggest an additional Bayesian method which generates a segmented classification concurrently with improving reconstructions of a set of registered images. A synthetic example is used to demonstrate the subjectives and benefits of this proposed approach. Two medical applications, one fusing computed tomography (CT) and single photon emission computed tomography (SPECT) brain scans, and the other magnetic resonance (MR) images at two different resolutions, are considered.     

An unbiased parametric imaging algorithm for nonuniformly sampled biomedical system parameter estimation

An unbiased algorithm of generalized linear least squares (GLLS) for parameter estimation of nonuniformly sampled biomedical systems is proposed. The basic theory and detailed derivation of the algorithm are given. This algorithm removes the initial values required and computational burden of nonlinear least regression and achieves a comparable estimation quality in terms of the estimates' bias and standard deviation. Therefore, this algorithm is particular useful in image-wide (pixel-by-pixel based) parameter estimation, e.g., to generate parametric images from tracer dynamic studies with positron emission tomography. An example is presented to demonstrate the performance of this new technique. This algorithm is also generally applicable to other continuous system parameter estimation.     

DNA biosensor for the detection of hydrazines

A double-stranded (ds) DNA-coated carbon paste electrode is employed as a remarkably sensitive biosensor for the detection of hydrazine compounds. The sensor relies on monitoring changes in the intrinsic anodic response of the surface-confined DNA resulting from its interaction with hydrazine compounds and requires no label or indicator. Short reaction times (1-10 min) are sufficient for monitoring part-per-billion levels of different hydrazines. Applicability to untreated natural water samples is illustrated. The response mechanism is discussed, along with prospects of using DNA biosensors for quantitaing other important molecules and elucidating DNA interactions and damage.     

Density and solubility of nafion: recast, annealed, and commercial films

The density of Nafion membranes wetted in water and acetonitrile and the solubility of Nafion in a 50:50 ethanol/water mixture are reported. Commercially available membranes, solution recast membranes, and recast membranes thermally processed for varying lengths of time were examined. Unheated recast membranes were found to be ～20% less dense in water than both commercial membranes and recast membranes heated at 140 °C for 40, 50, and 60 min. For heating times of ≥40 min, the density of recast membranes in water was invariant and equal to the density of commercial films. Similarly, in acetonitrile, commercial membranes and films heated for 1 h had the same density; unheated recast films were ～25% less dense. Nafion density in acetonitrile was ～15% less than that in water. Acid pretreatment reduced Nafion film density by ～15%. Unheated recast films were 22-100% soluble in a sonicated ethanol/water mixture. Commercial membranes and recast films heated for as little as 10 min were insoluble under the same conditions.