900 research outputs found

    surface interpolation and 3d relatability

    Get PDF
    Although the role of surface-level processes has been demonstrated, visual interpolation models often emphasize contour relationships. We report two experiments on geometric constraints governing 3D interpolation between surface patches without visible edges. Observers were asked to classify pairs of planar patches specified by random dot disparities and visible through circular apertures (aligned or misaligned) in a frontoparallel occluder. On each trial, surfaces appeared in parallel or converging planes with vertical (in Experiment 1) or horizontal (in Experiment 2) tilt and variable amounts of slant. We expected the classification task to be facilitated when patches were perceived as connected. We found enhanced sensitivity and speed for 3D relatable vs. nonrelatable patches. Here 3D relatability does not involve oriented edges but rather inducing patches' orientations computed from stereoscopic information. Performance was markedly affected by slant anisotropy: both sensitivity and speed were worse for patches with horizontal tilt. We found nearly identical advantages of 3D relatability on performance, suggesting an isotropic unit formation process. Results are interpreted as evidence that inducing slant constrains surface interpolation in the absence of explicit edge information: 3D contour and surface interpolation processes share common geometric constraints as formalized by 3D relatability

    Optimization of carbon and energy utilization through differential translational efficiency.

    Get PDF
    Control of translation is vital to all species. Here we employ a multi-omics approach to decipher condition-dependent translational regulation in the model acetogen Clostridium ljungdahlii. Integration of data from cells grown autotrophically or heterotrophically revealed that pathways critical to carbon and energy metabolism are under strong translational regulation. Major pathways involved in carbon and energy metabolism are not only differentially transcribed and translated, but their translational efficiencies are differentially elevated in response to resource availability under different growth conditions. We show that translational efficiency is not static and that it changes dynamically in response to mRNA expression levels. mRNAs harboring optimized 5'-untranslated region and coding region features, have higher translational efficiencies and are significantly enriched in genes encoding carbon and energy metabolism. In contrast, mRNAs enriched in housekeeping functions harbor sub-optimal features and have lower translational efficiencies. We propose that regulation of translational efficiency is crucial for effectively controlling resource allocation in energy-deprived microorganisms

    Collective and independent-particle motion in two-electron artificial atoms

    Full text link
    Investigations of the exactly solvable excitation spectra of two-electron quantum dots with a parabolic confinement, for different values of the parameter R_W expressing the relative magnitudes of the interelectron repulsion and the zero-point kinetic energy of the confined electrons, reveal for large R_W a remarkably well-developed ro-vibrational spectrum associated with formation of a linear trimeric rigid molecule composed of the two electrons and the infinitely heavy confining dot. This spectrum transforms to one characteristic of a "floppy" molecule for smaller values of R_W. The conditional probability distribution calculated for the exact two-electron wave functions allows for the identification of the ro-vibrational excitations as rotations and stretching/bending vibrations, and provides direct evidence pertaining to the formation of such molecules.Comment: Published version. Latex/Revtex, 5 pages with 2 postscript figures embedded in the text. For related papers, see http://www.prism.gatech.edu/~ph274c

    Landmark Detection in Cardiac MRI Using a Convolutional Neural Network

    Get PDF
    Purpose: To develop a convolutional neural network (CNN) solution for landmark detection in cardiac MRI. / Materials and Methods: This retrospective study included cine, late-gadolinium enhancement (LGE), and T1 mapping scans from two hospitals. The training set included 2329 patients (34019 images; mean age 54.1 years; 1471 men; December 2017-March 2020). A hold-out test set included 531 patients (7723 images; mean age 51.5 years, 323 men; May 2020-July 2020). CNN models were developed to detect two mitral valve plane and apical points on long-axis images. On short-axis images, anterior and posterior right ventricular insertion points and left ventricle center were detected. Model outputs were compared with manual labels by two readers. The trained model was deployed to MR scanners. / Results: For the long-axis images, successful detection of cardiac landmarks ranged from 99.7% to 100% for cine images and from 99.2% to 99.5% for LGE images. For the short-axis, detection rates was 96.6% for cine, 97.6% for LGE, and 98.9% for T1-mapping. The Euclidean distances between model and manual labels ranged from 2 to 3.5 mm for different landmarks, indicating close agreement between model landmarks to manual labels. No differences were found for the anterior right ventricular insertion angle and left ventricle length by the models and readers for all views and imaging sequences. Model inference on MR scanner took 610 msec on the graphics processing unit and 5.6 sec on central processing unit, respectively, for a typical cardiac cine series. / Conclusion: A CNN was developed for landmark detection in both long and short-axis cardiac MR images for cine, LGE and T1 mapping sequences, with the accuracy comparable to the interreader variation

    Bright-blood and dark-blood phase sensitive inversion recovery late gadolinium enhancement and T1 and T2 maps in a single free-breathing scan: an all-in-one approach

    Get PDF
    Background: Quantitative cardiovascular magnetic resonance (CMR) T1 and T2 mapping are used to detect diffuse disease such as myocardial fibrosis or edema. However, post gadolinium contrast mapping often lacks visual contrast needed for assessment of focal scar. On the other hand, late gadolinium enhancement (LGE) CMR which nulls the normal myocardium has excellent contrast between focal scar and normal myocardium but has poor ability to detect global disease. The objective of this work is to provide a calculated bright-blood (BB) and dark-blood (DB) LGE based on simultaneous acquisition of T1 and T2 maps, so that both diffuse and focal disease may be assessed within a single multi-parametric acquisition. // Methods: The prototype saturation recovery-based SASHA T1 mapping may be modified to jointly calculate T1 and T2 maps (known as multi-parametric SASHA) by acquiring additional saturation recovery (SR) images with both SR and T2 preparations. The synthetic BB phase sensitive inversion recovery (PSIR) LGE may be calculated from the post-contrast T1, and the DB PSIR LGE may be calculated from the post-contrast joint T1 and T2 maps. Multi-parametric SASHA maps were acquired free-breathing (45 heartbeats). Protocols were designed to use the same spatial resolution and achieve similar signal-to-noise ratio (SNR) as conventional motion corrected (MOCO) PSIR. The calculated BB and DB LGE were compared with separate free breathing (FB) BB and DB MOCO PSIR acquisitions requiring 16 and 32 heart beats, respectively. One slice with myocardial infarction (MI) was acquired with all protocols within 4 min. // Results: Multiparametric T1 and T2 maps and calculated BB and DB PSIR LGE images were acquired for patients with subendocardial chronic MI (n = 10), acute MI (n = 3), and myocarditis (n = 1). The contrast-to-noise (CNR) between scar (MI and myocarditis) and remote was 26.6 ± 7.7 and 20.2 ± 7.4 for BB and DB PSIR LGE, and 31.3 ± 10.6 and 21.8 ± 7.6 for calculated BB and DB PSIR LGE, respectively. The CNR between scar and the left ventricualr blood pool was 5.2 ± 6.5 and 29.7 ± 9.4 for conventional BB and DB PSIR LGE, and 6.5 ± 6.0 and 38.6 ± 11.6 for calculated BB and DB PSIR LGE, respectively. // Conclusions: A single free-breathing acquisition using multi-parametric SASHA provides T1 and T2 maps and calculated BB and DB PSIR LGE images for comprehensive tissue characterization
    corecore