PubMed · 8108747
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M Andjelkovic, F Dorchies. 1993. [Electrocardiography: errors and artifacts].. https://pubmed.ncbi.nlm.nih.gov/8108747/
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MOTIVATION: 10x Genomics VisiumHD enables spatial transcriptomics at 2 µm × 2 µm resolution but exhibits slide-specific, non-periodic striping artifacts due to lane-width variability. These multiplicative row/column effects distort bin total counts and can bias downstream analyses. The state-of-the-art destriping approach is the normalization procedure used as a preprocessing step in bin2cell; it applies sequential high-quantile row- then column-wise normalization, which is asymmetric and can introduce edge effects/macro-stripes and distortions of large-scale total-count structure. RESULTS: We propose a statistical destriping approach that leverages nuclei segmentation from the co-registered H&E image. Assuming transcript abundance is constant within each nucleus, we model bin counts with a negative binomial distribution whose mean is a product of a nucleus-specific concentration and row- and column-specific stripe-factors reflecting lane-width variation. We fit all parameters in a generalized linear modeling framework with cross-validated regularization on stripe-factors and iterative dispersion estimation, and use the fitted parameters to correct the observed counts into a destriped image. On synthetic data with known ground truth, our method improves stripe-factor estimation accuracy and reduces error in corrected counts relative to bin2cell and bin2cell-derived baselines. Across four public VisiumHD slides, it consistently lowers striping intensity while substantially better preserving biological signal present in the large-scale global count structure and avoiding the artifacts introduced by other methods. AVAILABILITY AND IMPLEMENTATION: All source code and links to publicly available data used for this study are available at https://github.com/paolamalsot/destriping-GLM.
We present an analytical approach that allows us to treat the long-time behavior of the recalling process in an oscillator neural network. It is well known that in coupled oscillatory neuronal systems, under suitable conditions, the original dynamics can be reduced to a simpler phase dynamics. In this description, the phases of the oscillators can be regarded as the timings of the neuronal spikes. To attempt an analytical treatment of the recalling dynamics of such a system, we study a simplified model in which we discretize time and assume a synchronous updating rule. The theoretical results show that the retrieval dynamics is described by recursion equations for some macroscopic parameters, such as an overlap with the retrieval pattern. We then treat the noise components in the local field, which arise from the learning of the unretrieved patterns, as gaussian variables. However, we take account of the temporal correlation between these noise components at different times. In particular, we find that this correlation is essential for correctly predicting the behavior of the retrieval process in the case of autoassociative memory. From the derived equations, the maximal storage capacity and the basin of attraction are calculated and graphically displayed. We also consider the more general case that the network retrieves an ordered sequence of phase patterns. In both cases, the basin of attraction remains sufficiently wide to recall the memorized pattern from a noisy one, even near saturation. The validity of these theoretical results is supported by numerical simulations. We believe that this model serves as a convenient starting point for the theoretical study of retrieval dynamics in general oscillatory systems.
STUDY DESIGN: Tantalum- and titanium-based lumbar interbody fusion devices were implanted into two fresh human cadavers, and magnetic resonance and computed tomographic imaging were performed to evaluate adjacent spinal structures and the amount of metallic artifact. OBJECTIVE: The objective of this study was to prospectively compare the preliminary results of magnetic resonance imaging and computed tomography scanning image quality after the implantation of both titanium and tantalum spinal implants. SUMMARY OF BACKGROUND DATA: The availability of tantalum and titanium spinal implants brings theoretical magnetic resonance imaging compatibility along with several other desirable characteristics. The magnetic resonance imaging and computed tomographic imaging of tantalum spinal instrumentation has never been studied previously or compared with titanium instrumentation. METHODS: Titanium and tantalum spinal implants produced for anterior spinal fusion were each placed at two levels in the lumbar spine of two fresh cadaver specimens. Sequential spin echo T1-weighted and T2-weighted magnetic resonance imaging studies and computed tomographic scans were obtained. The resulting images were then graded to describe and compare the behavior of tantalum metal in magnetic resonance imaging and computed tomographic studies. RESULTS: Good T1 and T2 images were obtained that allowed visualization of the neural structures with minimal artifact. The optimal T1 images for tantalum metal were similar in quality to the optimal T1 parameters for titanium metal. T2 images for both tantalum and titanium metal were obtained with similar results for both metals. Gradient echo magnetic resonance imaging scans of both were poorly imaged with a large amount of artifact. Computed tomographic studies of tantalum implants produced a large amount of metal artifact when compared with computed tomographic studies of titanium implants. CONCLUSIONS: High-quality magnetic resonance imaging studies can be obtained after the implantation of both titanium and tantalum spinal instrumentation. Both of the metals produce similar images on magnetic resonance imaging studies with comparable amounts of metallic artifact. High-quality computed tomographic scans of titanium implants can be obtained with minimal distortion secondary to artifact. However, computed tomographic scanning is not the imaging modality of choice for the tantalum spinal implants because of the large amounts of artifact.