Utility of multispectral imaging for nuclear classification of routine clinical histopathology imagery

<p>Abstract</p> <p>Background</p> <p>We present an analysis of the utility of multispectral versus standard RGB imagery for routine H&E stained histopathology images, in particular for pixel-level classification of nuclei. Our multispectral imagery has 29 spectral bands, spaced 10 nm within the visual range of 420–700 nm. It has been hypothesized that the additional spectral bands contain further information useful for classification as compared to the 3 standard bands of RGB imagery. We present analyses of our data designed to test this hypothesis.</p> <p>Results</p> <p>For classification using all available image bands, we find the best performance (equal tradeoff between detection rate and false alarm rate) is obtained from either the multispectral or our "ccd" RGB imagery, with an overall increase in performance of 0.79% compared to the next best performing image type. For classification using single image bands, the single best multispectral band (in the red portion of the spectrum) gave a performance increase of 0.57%, compared to performance of the single best RGB band (red). Additionally, red bands had the highest coefficients/preference in our classifiers. Principal components analysis of the multispectral imagery indicates only two significant image bands, which is not surprising given the presence of two stains.</p> <p>Conclusion</p> <p>Our results indicate that multispectral imagery for routine H&E stained histopathology provides minimal additional spectral information for a pixel-level nuclear classification task than would standard RGB imagery.</p

Solulin reduces infarct volume and regulates gene-expression in transient middle cerebral artery occlusion in rats

<p>Abstract</p> <p>Background</p> <p>Thrombolysis after acute ischemic stroke has only proven to be beneficial in a subset of patients. The soluble recombinant analogue of human thrombomodulin, Solulin, was studied in an <it>in vivo </it>rat model of acute ischemic stroke.</p> <p>Methods</p> <p>Male SD rats were subjected to 2 hrs of transient middle cerebral artery occlusion (tMCAO). Rats treated with Solulin intravenously shortly before reperfusion were compared to rats receiving normal saline i.v. with respect to infarct volumes, neurological deficits and mortality. Gene expression of IL-6, IL-1β, TNF-α, MMP-9, CD11B and GFAP were semiquantitatively analyzed by rtPCR of the penumbra.</p> <p>Results</p> <p>24 hrs after reperfusion, rats were neurologically tested, euthanized and infarct volumes determined. Solulin significantly reduced mean total (p = 0.001), cortical (p = 0.002), and basal ganglia (p = 0.036) infarct volumes. Hippocampal infarct volumes (p = 0.191) were not significantly affected. Solulin significantly downregulated the expression of IL-1β (79%; p < 0.001), TNF-α (59%; p = 0.001), IL-6 (47%; p = 0.04), and CD11B (49%; p = 0.001) in the infarcted cortex compared to controls.</p> <p>Conclusions</p> <p>Solulin reduced mean total, cortical and basal ganglia infarct volumes and regulated a subset of cytokines and proteases after tMCAO suggesting the potency of this compound for therapeutic interventions.</p

Statistical Texture Characterization From Discrete Wavelet Representations

We conjecture that texture can be characterized by the statistics of the wavelet detail coefficients and therefore introduce 2 feature sets: 1) the wavelet histogram signatures which capture all first order statistics using a model based approach; 2) the wavelet cooccurrence signatures, which reflect the coefficients&apos; second order statistics. The introduced feature sets outperform the traditionally used energy. Best performance is achieved by combining histogram and cooccurrence signatures

Wavelet Correlation Signatures for Color Texture Characterization

In the last decade, multiscale techniques for gray-level texture analysis have been intensively used. In this paper, we aim on extending these techniques to color images. Weintroduce wavelet energy-correlation signatures and we derive the transformation of these signatures upon linear color space transformations. Experiments are conducted on a set of 30 natural colored texture images in which color and graylevel texture classi#cation performances are compared. It is demonstrated that the wavelet correlation features contain more information than the intensity or the energy features of each color plane separately. The in#uence of image representation in color space is evaluated. Key words: texture analysis, classi#cation, color spaces, feature extraction, wavelet signatures 1 Introduction For image analysis, color and texture are two of the most important properties, especially when one is dealing with real world images. Classical image analysis schemes only takeinto account the pix..

A multiparametric assay for quantitative nerve regeneration evaluation

We introduce an assay for the semi-automated quantification of nerve regeneration by image analysis. Digital images of histological sections of regenerated nerves are recorded using an automated inverted microscope and merged into high-resolution mosaic images representing the entire nerve. These are analysed by a dedicated image-processing package that computes nerve-specific features (e.g. nerve area, fibre count, myelinated area) and fibre-specific features (area, perimeter, myelin sheet thickness). The assay's performance and correlation of the automatically computed data with visually obtained data are determined on a set of 140 semithin sections from the distal part of a rat tibial nerve from four different experimental treatment groups (control, sham, sutured, cut) taken at seven different time points after surgery. Results show a high correlation between the manually and automatically derived data, and a high discriminative power towards treatment. Extra value is added by the large feature set. In conclusion, the assay is fast and offers data that currently can be obtained only by a combination of laborious and time-consuming tests.status: publishe