22 research outputs found
Comparison of the average ventilator-measured volume and the total volume from the volume maps for six untreated rats, plotted as a function of tracheal pressure.
<p>Error bars represent the standard deviation of the mean ventilator volume and tracheal pressure over the entire imaging experiment.</p
An example of finite element discretization of an image.
<p>An example of finite element discretization of an image.</p
Examples of image processing for registration testing.
<p>A) Original image. B) Image with bones removed. C) Image with all background masked. D) Same as C, with Gaussian filter applied prior to masking. E) Same as D, with contrast enhancement applied.</p
Representative pressure-volume curves made from the total volume from the volume maps and average tracheal pressure.
<p>Data are from three different rats, one from each dose group.</p
Block diagram illustrating the data processing flow.
<p>Block diagram illustrating the data processing flow.</p
Average landmark displacement (in pixels, red) and the percentage of misregistered landmarks (blue) for the five cases shown in Figure 1.
<p>The red dashed line indicates the observer’s average “click error”.</p
Automated Platform for High-Resolution Tissue Imaging Using Nanospray Desorption Electrospray Ionization Mass Spectrometry
An automated platform has been developed for acquisition
and visualization of mass spectrometry imaging (MSI) data using nanospray
desorption electrospray ionization (nano-DESI). The new system enables
robust operation of the nano-DESI imaging source over many hours by
precisely controlling the distance between the sample and the nano-DESI
probe. This is achieved by mounting the sample holder onto an automated <i>XYZ</i> stage, defining the tilt of the sample plane, and recalculating
the vertical position of the stage at each point. This approach is
useful for imaging of relatively flat samples such as thin tissue
sections. Custom software called MSI QuickView was developed for visualization
of large data sets generated in imaging experiments. MSI QuickView
enables fast visualization of the imaging data during data acquisition
and detailed processing after the entire image is acquired. The performance
of the system is demonstrated by imaging rat brain tissue sections.
Low background noise enables simultaneous detection of lipids and
metabolites in the tissue section. High-resolution mass analysis combined
with tandem mass spectometry (MS/MS) experiments enabled identification
of the observed species. In addition, the high dynamic range (>2000)
of the technique allowed us to generate ion images of low-abundance
isobaric lipids. A high-spatial resolution image was acquired over
a small region of the tissue section revealing the distribution of
an abundant brain metabolite, creatine, on the boundary between the
white and gray matter. The observed distribution is consistent with
the literature data obtained using magnetic resonance spectroscopy
Representative H&E stained images from a control mouse (A) and a smoke-exposed mouse (B).
<p>Color maps of each image, (C) and (D) respectively, are shown to illustrate the different airspaces. The bars are 200 µm.</p
Automated vs. manual calculation of the mean equivalent diameter D<sub>0</sub> (top) and weighted index D<sub>2</sub> (bottom) from 20 randomly selected images.
<p>In spite of the subtle differences between thresholding methods (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0006670#pone-0006670-g004" target="_blank">Figure 4</a>), the strong correlations indicate that there are no statistically significant differences between measurement techniques.</p
Automated steps for processing H&E stained images prior to calculating D<sub>2</sub>.
<p>A) RGB color image acquired at 200Ă—magnification. B) Green-channel of A. C) Localized background intensity normalization performed on B. D) Threshold of intensity converts C to a binary image. E) Small black particles removed from D. F) Small white particles removed from E.</p