PubMed · 15335207
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Jeffrey Scott Coker, Eric Davies. 2004. Identifying adaptor contamination when mining DNA sequence data.. https://doi.org/10.2144/04372bm03
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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.
To compare the effect of different reconstruction kernels and a noise-reducing postprocessing filter on the delineation of coronary artery stents in 16-slice CT-angiography. Ten patients with coronary stents (seven LAD, five RCX and three RCA) were examined with a 16-slice MDCT using standard acquisition parameters. Images were reconstructed using a medium soft (B30f) and a dedicated, edge-enhancing kernel (B46f). Additional postprocessing with an edge-preserving filter was performed on B46f images to reduce the image noise. In multiplanar reformations (MPRs) along and perpendicular to the stent axis, intraluminal attenuation values and the visible lumen diameter were measured. Image noise was measured in the subcutaneous fat using a region of interest (ROI) technique. Arterial enhancement in the aorta was 275.1 HU. Attenuation in the stent lumen was 390.4, 340.0 and 346.8 HU in MPRs derived from B30f, original B46 and postprocessed B46f images. The mean noise level was 20.4, 35.0 and 24.9 HU respectively. The visible lumen diameter was significantly greater in B46f and postprocessed B46f images (2.17 and 2.16 mm), compared to 1.93 mm in B30f images (p<0.01). Edge-enhancing reconstruction kernels increase the visible stent lumen, but also increase image noise. Dedicated postprocessing filters can reduce the introduced noise without a loss of spatial resolution.
BACKGROUND: Flexible video bronchoscopes, in particular the Olympus BF Type 3C160, are commonly used in pediatric respiratory medicine. There is no data on the magnification and distortion effects of these bronchoscopes yet important clinical decisions are made from the images. The aim of this study was to systematically describe the magnification and distortion of flexible bronchoscope images taken at various distances from the object. METHODS: Using images of known objects and processing these by digital video and computer programs both magnification and distortion scales were derived. RESULTS: Magnification changes as a linear function between 100 mm (x1) and 10 mm (x9.55) and then as an exponential function between 10 mm and 3 mm (x40) from the object. Magnification depends on the axis of orientation of the object to the optic axis or geometrical axis of the bronchoscope. Magnification also varies across the field of view with the central magnification being 39% greater than at the periphery of the field of view at 15 mm from the object. However, in the paediatric situation the diameter of the orifices is usually less than 10 mm and thus this limits the exposure to these peripheral limits of magnification reduction. Intraclass correlations for measurements and repeatability studies between instruments are very high, r = 0.96. Distortion occurs as both barrel and geometric types but both types are heterogeneous across the field of view. Distortion of geometric type ranges up to 30% at 3 mm from the object but may be as low as 5% depending on the position of the object in relation to the optic axis. CONCLUSION: We conclude that the optimal working distance range is between 40 and 10 mm from the object. However the clinician should be cognisant of both variations in magnification and distortion in clinical judgements.