Color Intensity Projections: A simple way to display changes in astronomical images

To detect changes in repeated astronomical images of the same field of view (FOV), a common practice is to stroboscopically switch between the images. Using this method, objects that are changing in location or intensity between images are easier to see because they are constantly changing. A novel display method, called arrival time color intensity projections (CIPs), is presented that combines any number of grayscale images into a single color image on a pixel by pixel basis. Any values that are unchanged over the grayscale images look the same in the color image. However, pixels that change over the grayscale image have a color saturation that increases with the amount of change and a hue that corresponds to the timing of the changes. Thus objects moving in the grayscale images change from red to green to blue as they move across the color image. Consequently, moving objects are easier to detect and assess on the color image than on the grayscale images. A sequence of images of a comet plunging into the sun taken by the SOHO satellite (NASA/ESA) and Hubble Space Telescope images of a trans-Neptunian object (TNO) are used to demonstrate the method.Comment: 9 pages, 2 figures. Accepted for publication in Publications of the Astronomical Society of the Pacific. The quality of figure 1 been improved from the previous posted versio

A robust and reliable method for detecting signals of interest in multiexponential decays

The concept of rejecting the null hypothesis for definitively detecting a signal was extended to relaxation spectrum space for multiexponential reconstruction. The novel test was applied to the problem of detecting the myelin signal, which is believed to have a time constant below 40ms, in T2 decays from MRI's of the human brain. It was demonstrated that the test allowed the detection of a signal in a relaxation spectrum using only the information in the data, thus avoiding any potentially unreliable prior information. The test was implemented both explicitly and implicitly for simulated T2 measurements. For the explicit implementation, the null hypothesis was that a relaxation spectrum existed that had no signal below 40ms and that was consistent with the T2 decay. The confidence level by which the null hypothesis could be rejected gave the confidence level that there was signal below the 40ms time constant. The explicit implementation assessed the test's performance with and without prior information where the prior information was the nonnegative relaxation spectrum assumption. The test was also implemented implicitly with a data conserving multiexponential reconstruction algorithm that used left invertible matrices and that has been published previously. The implicit and explicit implementations demonstrated similar characteristics in detecting the myelin signal in both the simulated and experimental T2 decays, providing additional evidence to support the close link between the two tests. [Full abstract in paper]Comment: 23 pages with 8 figure

Accelerating regional atrophy rates in the progression from normal aging to Alzheimer’s disease

We investigated progression of atrophy in vivo, in Alzheimer’s disease (AD), and mild cognitive impairment (MCI). We included 64 patients with AD, 44 with MCI and 34 controls with serial MRI examinations (interval 1.8 ± 0.7 years). A nonlinear registration algorithm (fluid) was used to calculate atrophy rates in six regions: frontal, medial temporal, temporal (extramedial), parietal, occipital lobes and insular cortex. In MCI, the highest atrophy rate was observed in the medial temporal lobe, comparable with AD. AD patients showed even higher atrophy rates in the extramedial temporal lobe. Additionally, atrophy rates in frontal, parietal and occipital lobes were increased. Cox proportional hazard models showed that all regional atrophy rates predicted conversion to AD. Hazard ratios varied between 2.6 (95% confidence interval (CI) = 1.1–6.2) for occipital atrophy and 15.8 (95% CI = 3.5–71.8) for medial temporal lobe atrophy. In conclusion, atrophy spreads through the brain with development of AD. MCI is marked by temporal lobe atrophy. In AD, atrophy rate in the extramedial temporal lobe was even higher. Moreover, atrophy rates also accelerated in parietal, frontal, insular and occipital lobes. Finally, in nondemented elderly, medial temporal lobe atrophy was most predictive of progression to AD, demonstrating the involvement of this region in the development of AD