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At least 235 records · Page 13Linked to original sources
PubMed2002

Improved parametric image generation using spatial-temporal analysis of dynamic PET studies.

The value of parametric images that represent both spatial distribution and quantification of the physiological parameters of tracer kinetics has long been recognized. However, the inherent high noise level of pixel kinetics of dynamic PET makes it unsuitable to generate parametric images of the microparameters of tracer kinetic model by conventional weighted nonlinear least squares (WNLS) fitting. Based on the concept that both spatial and temporal information should be integrated to improve parametric image quality, a nonlinear ridge regression with spatial constraint (NLRRSC) parametric imaging algorithm was proposed in this study. For NLRRSC, a term that penalizes local spatial variation of parameters was added to the cost function of WNLS fitting. The initial estimates and spatial constraint were estimated by component representation model (CRM) with cluster analysis. A hierarchical cluster with average linkage method was used to extract components. The ridge parameter was determined by linear ridge regression theory at each iteration, and a modified Gauss-Newton algorithm was used for minimizing the cost function. Results from a computer simulation showed that the percent mean square error of estimates obtained by NLRRSC can be decreased by 60-80% compared to that of WNLS. The parametric images estimated by NLRRSC are significantly better than the ones generated by WNLS. A highly correlated linear relationship was found between the ROI values calculated from the microparametric images generated by NLRRSC and estimates from ROI kinetic fitting. NLRRSC provided a reliable estimate of glucose metabolite uptake rate with a comparable image quality compared to Patlak analysis. In conclusion, NLRRSC is a reliable and robust parametric imaging algorithm for dynamic PET studies.

Algorithms↗
PubMedDate not supplied

Mitochondrial DNA variation in the European otter (Lutra lutra) and the use of spatial autocorrelation analysis in conservation.

To add genetic information to the international conservation efforts on European otters Lutra lutra, we investigated the genetic population structure in and around a known "source" population of the otter, the Oberlausitz (OL) in eastern Germany. This was complemented by a first survey of genetic variation levels in the Central European otter population. Sequence analysis of 300bp of the mitochondrial control region in 76 specimens from the eastern German study region and 53 individuals from several other European populations revealed a low level of genetic variation, with only 5 haplotypes present and nucleotide diversities within populations ranging from 0.00% to 0.17%. Apart from eastern Germany, one haplotype was by far the most abundant one, from which other, only locally occurring types, could be derived by a single point mutation. This suggests a single Pleistocene refugium from which the analyzed European regions have been reinvaded after the glaciations. Within eastern Germany, two abundant haplotypes were found. Their occurrence differed significantly among subregions of eastern Germany. The uneven distribution of a locally restricted but abundant haplotype could be explained by isolation-by-distance and might reflect emigration from the OL source population to surrounding regions. This suggests that vital local populations can indeed serve as "sources" for the invasion of surrounding areas. Given a suitable genetic marker, we suggest a spatial autocorrelation analysis to monitor the genetic effect of such an emigration from a source population.

Animals↗
PubMed1989

Spatial autocorrelation analysis of the distribution of genotypes within populations of lodgepole pine.

Spatial autocorrelation analyses of point samples within two populations of lodgepole pine (Pinus contorta ssp. latifolia) indicate that single-locus mature tree and pollen genotypes are distributed in a nearly random fashion for most of the allozyme loci assayed. This lack of structure in the distributions of most genotypes is consistent with outcrossing rates that are very nearly 1.0 and with estimates indicating that both pollen and seed are dispersed over long distances in lodgepole pine. However, spatial autocorrelation of genotypes for a few loci suggests that genotypes at these loci may be under natural selection.

Alleles↗
PubMed2003

Localization of human somatosensory cortex using spatially filtered magnetoencephalography.

A spatial filter algorithm based on minimum-variance beamforming (synthetic aperture magnetometry (SAM)) was applied to single trial neuromagnetic recordings in order to localize primary somatosensory cortex. Magnetoencephalography (MEG) responses to electrical stimulation of the right and left median nerve were recorded using a whole-head MEG system and localized using both SAM spatial filtering and dipole analysis. Spatial filtering was applied to single trial neuromagnetic recordings to produce 3-dimensional difference images of source power between active (0-50 ms) and control states (-50-0 ms) in the range of 15-300 Hz. Average difference between N20m dipole location and location of maximal increase in power in the SAM images was 3.7 mm (1.5 mm SD) and localized to primary somatosensory cortex. Time-frequency analysis of spatially filtered output for the peak SAM locations showed a brief (10 ms) increase in the 60-100 Hz band coincident with the N20m response and a longer duration (approx. 80 ms) increase in power in the 10-40 Hz band following N20m onset. These results indicate that beamformer based spatial filter methods such as SAM can be used to localize temporally discrete cortical activity produced by median nerve stimulation.

Adult↗
PubMed1986

Spatial resolution analysis of computed tomographic images.

Methods are presented for the quantification of spatial resolution in x-ray computed tomographic (CT) images. Model-dependent methods are derived and compared with model independent methods for computation of the Modulation Transfer Function (MTF). These techniques are applied to phantom images of point, line, edge, and ring discontinuities. The model-dependent methods utilize multiparameter fits of a two-dimensional model function to the image data. Model predictions are compared with results obtained in a model-independent way by numerical transformation of the data. Results of resolution measurements of an Imatron C-100 CT scanner at UCSF and a second experimental scanner at the UCSF Physics Research Laboratory are presented.

Humans↗
PubMed2003

Spatial distribution analysis of AT- and GC-rich regions in nuclei using corrected fluorescence resonance energy transfer.

We employed microscopic intensity-based fluorescence resonance energy transfer (FRET) images with correction by donor and acceptor concentrations to obtain unbiased maps of spatial distribution of the AT- and GC-rich DNA regions in nuclei. FRET images of 137 bovine aortic endothelial cells stained by the AT-specific donor Hoechst 33258 and the GC-specific acceptor 7-aminoactinomycin D were acquired and corrected for the donor and acceptor concentrations by the Gordon's method based on the three fluorescence filter sets. The corrected FRET images were quantitatively analyzed by texture analysis to correlate the spatial distribution of the AT- and GC-rich DNA regions with different phases of the cell cycle. Both visual observation and quantitative texture analysis revealed an increased number and size of the low FRET efficiency centers for cells in the G(2)/M-phases, compared to the G(1)-phase cells. We have detected cell cycle-dependent changes of the spatial organization and separation of the AT- and GC-rich DNA regions. Using the corrected FRET (cFRET) technique, we were able to detect early DNA separation stages in late interphase nuclei.

AT Rich Sequence↗
PubMed1991

Spatial Fourier analysis of video photobleaching measurements. Principles and optimization.

The major use of the fluorescence recovery after photobleaching (FRAP) technique is to measure the translational motion of the molecular components in various condensed media. In a conventional laser spot photobleaching experiment, a photomultiplier is used to measure the total brightness levels of the bleached region in the sample, so no spatial information can be directly obtained. In video-FRAP, a series of images after photobleaching is acquired, allowing the spatial character of the recovery to be determined; this permits direct detection of both anisotropic diffusion and flow. To utilize all of the available image data to determine the transport coefficients, a two-dimensional spatial Fourier transform analysis of the images after photobleaching was employed. The change in the transform between two time points reflects the action of diffusion during the interim. An important advantage of this method, which involves taking the ratio of image transforms at different time points, is that it does not require a specific initial condition to be created by laser photobleaching. The ability of the analysis to extract transport coefficients from computer-simulated diffusional recovery is assessed in the presence of increasing amounts of noise. Experimental data analysis from the diffusion of proteins in viscous solutions and from the diffusion of protein receptors on cell surfaces demonstrate the feasibility of the Fourier analysis to obtain transport coefficients from the video FRAP measurement.

Biophysical Phenomena↗
PubMed1998

What is line bisection in unilateral spatial neglect? Analysis of perceptual and motor aspects in line bisection tasks.

Three patients with unilateral spatial neglect could detect the difference of length between the right and left segments when a line had a transection mark. To examine the effect of response mode, the manual line bisection task and a new "line bisection task by fixation" were given to the patients. In tasks that used lines with no landmark, they showed apparent rightward errors. The results suggest that line bisection is not a task that examines the ability of patients with neglect to compare the right and left extents of a line. Where to fixate as the subjective midpoint may determine the rightward errors of bisection, whether manual response is used or not.

Aged↗
PubMed1998

How to "hear" visual disparities: real-time stereoscopic spatial depth analysis using temporal resonance.

In a stereoscopic system, both eyes or cameras have a slightly different view. As a consequence, small variations between the projected images exist ('disparities') which are spatially evaluated in order to retrieve depth information (Sanger 1988; Fleet et al. 1991). A strong similarity exists between the analysis of visual disparities and the determination of the azimuth of a sound source (Wagner and Frost 1993). The direction of the sound is thereby determined from the temporal delay between the left and right ear signals (Konishi and Sullivan 1986). Similarly, here we transpose the spatially defined problem of disparity analysis into the temporal domain and utilize two resonators implemented in the form of causal (electronic) filters to determine the disparity as local temporal phase differences between the left and right filter responses. This approach permits real-time analysis and can be solved analytically for a step function contrast change, which is an important case in all real-world applications. The proposed theoretical framework for spatial depth retrieval directly utilizes a temporal algorithm borrowed from auditory signal analysis. Thus, the suggested similarity between the visual and the auditory system in the brain (Wagner and Frost 1993) finds its analogy here at the algorithmical level. We will compare the results from the temporal resonance algorithm with those obtained from several other techniques like cross-correlation or spatial phase-based disparity estimation showing that the novel algorithm achieves performances similar to the 'classical' approaches using much lower computational resources.

Algorithms↗
PubMed1986

Space and spatial frequency: analysis and representation in the macaque striate cortex.

Simple cells in the macaque striate cortex were tested with bars, edges and gratings. Spatial frequency tuning curves could be predicted from the spatial profiles plotted with bars and edges and the bandwidth could be evaluated more accurately by computing the mean from measured and predicted tuning curves. The results suggest that the mean relative spatial frequency bandwidth (delta f/fo) is nearly constant and of a moderate value. But at each optimal spatial frequency, cells with different bandwidths (about a factor of two) were recorded. The shapes of spatial response profiles resemble the corresponding spatial and spatial frequency characteristics of line and edge detectors evaluated psychophysically. Among the remaining cell types, concentric cells tend to be tuned to lower spatial frequencies and have broader bandwidths, whereas periodic cells prefer higher spatial frequencies and have narrower bandwidths. Thus the mean relative bandwidth tends to decrease significantly with spatial frequency (as required by a system of patch-by-patch Fourier analysis) only when cells with poor orientation selectivity and the non-linear silent periodic cells are included along with the simple cells. Simple cells, on their own, seem to form a quasi-linear contrast processing system which is more biased towards spatial accuracy than spatial frequency selectivity.

Animals↗
PubMed1982

Polarizing microscopy of Picrosirius stained bone sections as a method for analysis of spatial distribution of collagen fibers by optical diffractometry.

Cross sections of femur diaphysis obtained from control and osteopetrotic rats were stained with hematoxylin-eosin (HE) and Picrosirius (SR). Analogous selected areas of bone sections photographed under a polarizing microscope were analysed by optical diffractometry. Since the collagen fibers are a good marker for the structure of bone tissue, their spatial distribution evaluated by optical diffractometry provides information on the tissue architecture. The Picrosirius staining technique enhances the natural birefringency of collagen fibers. Therefore, in the polarizing microscope, pictures of high contrast are obtained. This procedure, by increasing the amount of information in the image, increases the quantity of the data obtained by optical diffractometry in comparison with the HE staining method. The results obtained prove that SR staining combined with polarizing microscopy might be useful for optical diffractometry in analysis of the spatial distribution of collagen fibers in all connective tissues, where they could serve as markers of tissue architecture.

Animals↗
PubMed1989

[The geographical distribution of fertility around Mexico City].

A spatial analysis of fertility around Mexico City reveals an "inverted U" pattern which appears, on the face of it, inconsistent with both conventional economic location analysis and a spatial diffusion process. A closer examination of the problem implies that economic variables, when integrated in a proper model, may account for the observed cross- sectional spatial pattern, whereas pure diffusion can not. Spatial diffusion, however, may be responsible at least in part for the observed fertility changes over time. The geographical patterns of fertility in 2 states neighboring Mexico City (Mexico and Hidalgo) are examined empirically. The interpretation of the nonmonotonic distance effect is that there are significant locational advantages to childbearing at medium distances that are not enjoyed at households location either very close or far away from the city.

Americas↗
PubMed1999

Spatial autocorrelation analysis of individual multiallele and multilocus genetic structure.

Population genetic theory predicts that plant populations will exhibit internal spatial autocorrelation when propagule flow is restricted, but as an empirical reality, spatial structure is rarely consistent across loci or sites, and is generally weak. A lack of sensitivity in the statistical procedures may explain the discrepancy. Most work to date, based on allozymes, has involved pattern analysis for individual alleles, but new PCR-based genetic markers are coming into vogue, with vastly increased numbers of alleles. The field is badly in need of an explicitly multivariate approach to autocorrelation analysis, and our purpose here is to introduce a new approach that is applicable to multiallelic codominant, multilocus arrays. The procedure treats the genetic data set as a whole, strengthening the spatial signal and reducing the stochastic (allele-to-allele, and locus-to-locus) noise. We (i) develop a very general multivariate method, based on genetic distance methods, (ii) illustrate it for multiallelic codominant loci, and (iii) provide nonparametric permutational testing procedures for the full correlogram. We illustrate the new method with an example data set from the orchid Caladenia tentaculata, for which we show (iv) how the multivariate treatment compares with the single-allele treatment, (v) that intermediate frequency alleles from highly polymorphic loci perform well and rare alleles poorly, (vi) that a multilocus treatment provides clearer answers than separate single-locus treatments, and (vii) that weighting alleles differentially improves our resolution minimally. The results, though specific to Caladenia, offer encouragement for wider application.

Alleles↗
PubMed2001

Tissue harmonic image analysis based on spatial covariance.

The van Cittert-Zernike theorem has been widely used to describe spatial covariance of the pressure field backscattered from a speckle object. Spatial covariance contains important information in the context of correlation-based correction of sound velocity inhomogeneities. Previous work was primarily based on spatial covariance analysis for linear imaging. In this paper, we extend the analysis to tissue harmonic imaging. Specifically, we investigate effects of the signal-to-noise ratio (SNR) and sound velocity inhomogeneities on spatial covariance. Results from tissue harmonic imaging are also compared with those from linear imaging. Both simulations and experiments are performed. At high SNRs, although both linear imaging and tissue harmonic imaging have spatial covariance functions close to theory, the spatial covariance of tissue harmonic imaging is consistently lower than that of linear imaging regardless of the presence of sound velocity inhomogeneities. At low SNRs, on the other hand, spatial covariance of tissue harmonic imaging is significantly affected. Because the tissue harmonic signal is much weaker than the linear counterpart, the low SNR reduces the accuracy of correlation-based estimation. It is concluded that the linear signal is more suitable for correlation-based correction of sound velocity inhomogeneities, despite the fact that tissue harmonic imaging generally has improved image quality over linear imaging.

Ultrasonography↗
PubMed2025

Spatial transcriptomic analysis of mouse parathyroid gland cells expressing an activating variant of Gcm2.

Glial cells missing 2 (GCM2) is an essential transcription factor for the development of parathyroid glands. Germline GCM2 variants that repress or enhance transcriptional activity predispose a subset of patients to hypoparathyroidism or hyperparathyroidism, respectively. A recurrent germline heterozygous activating missense variant of GCM2, p.Y394S has been identified in some patients with primary hyperparathyroidism. A genetically engineered knock-in mouse model of this variant corresponding to p.Y392S in the mouse Gcm2 gene (Gcm2 +/Y392S) did not show obvious parathyroid tumors. However, in GCM2-binding site mediated luciferase reporter assays in HEK293 cells, the mouse and the human variant both exhibited enhanced transcriptional activity. Therefore, we assessed the effect of this variant on gene expression in vivo in parathyroid glands from Gcm2 +/Y392S and WT mice. Using the 10x Genomics Visium platform, spatially resolved transcriptomic analysis was performed on formalin-fixed and paraffin-embedded (FFPE) tracheal tissue sections of Gcm2 +/Y392S and WT mice to capture RNA from parathyroid glands together with other cell types in the tissue sections. Transcriptome sequence data analysis detected 8 different clusters in the tissue sections based on similarity of gene expression profiles. Cluster-1, which contained parathyroid gland cells expressing Pth and Gcm2, was further evaluated for transcripts that were differentially expressed more than 2-fold in Gcm2 +/Y392S compared to WT. Increased transcript level of Lgals3 (galectin-3) was seen in Gcm2 +/Y392S parathyroid gland cells which is among markers of parathyroid carcinoma. Galectin-3 protein was detected in available FFPE human parathyroid samples of patients with germline heterozygous activating GCM2 variants, p.Y394S (n = 4/10) or p.L379Q (n = 2/2). These results indicate a potential for growth and malignancy of parathyroid glands expressing GCM2 variants. The transcriptomic data of mouse parathyroid gland cells generated in this study can serve as a valuable resource for investigating genes and pathways in normal or abnormal parathyroid gland growth and physiology.

GCM2, gene↗
PubMed1987

Component analysis of spatial and spectral patterns in multispectral images. I. Basis.

A new (to our knowledge) theory of component pattern analysis in multispectral images is developed by using the methods of principal component analysis and nonlinear optimization with a nonnegativity constraint. Given images of a scene in different color bands, we estimate both the spectral curves of components included in the image and the spatial pattern corresponding to each spectral curve. In this method, neither spatial nor spectral features of the components are necessary, but the physical rule of nonnegative absorptivity and density nonnegativity is used for any material of any optical frequency at any position in the image. Experimental results of component analysis with real microscopic image data are shown to demonstrate the effectiveness of the proposed method.

Form Perception↗