Correction scheme for multiple correlated statistical tests in local shape analysis

2004 ◽  
Author(s):  
Martin A. Styner ◽  
Guido Gerig
Keyword(s):  
Shape Analysis ◽  
Statistical Tests ◽  
Local Shape ◽  
Correction Scheme

Simultaneous inversion for crustal thickness and anisotropy by multiphase splitting analysis of receiver functions

2020 ◽  
Vol 223 (3) ◽  
pp. 2009-2026
Author(s):  
Frederik Link ◽  
Georg Rümpker ◽  
Ayoub Kaviani
Keyword(s):  
Statistical Tests ◽  
Real Data ◽  
Crustal Thickness ◽  
Receiver Functions ◽  
S Wave ◽  
Arrival Times ◽  
Simultaneous Inversion ◽  
Correction Scheme ◽  
Converted Phases ◽  
Two Phases

SUMMARY We present a technique to derive robust estimates for the crustal thickness and elastic properties, including anisotropy, from shear wave splitting of converted phases in receiver functions. We combine stacking procedures with a correction scheme for the splitting effect of the crustal converted Ps-phase and its first reverberation, the PpPs-phase, where we also allow for a predefined dipping Moho. The incorporation of two phases stabilizes the analysis procedure and allows to simultaneously solve for the crustal thickness, the ratio of average P- to S-wave velocities, the percentage of anisotropy and the fast-axis direction. The stacking is based on arrival times and polarizations computed using a ray-based algorithm. Synthetic tests show the robustness of the technique and its applicability to tectonic settings where dip of the Moho is significant. These tests also demonstrate that the effects of a dipping layer boundary may overprint a possible anisotropic signature. To constrain the uncertainty of our results we perform statistical tests based on a bootstrapping approach. We distinguish between different model classes by comparing the coherency of the stacked amplitudes after moveout correction. We apply the new technique to real-data examples from different tectonic regimes and show that coherency of the stacked receiver functions can be improved, when anisotropy and a dipping Moho are included in the analysis. The examples underline the advantages of statistical analyses when dealing with stacking procedures and potentially ambiguous solutions.

Automated Segmentation Refinement of Small Lung Nodules in CT Scans by Local Shape Analysis

2011 ◽  
Vol 58 (12) ◽  
pp. 3418-3428 ◽  
Author(s):  
S. Diciotti ◽  
S. Lombardo ◽  
M. Falchini ◽  
G. Picozzi ◽  
M. Mascalchi
Keyword(s):  
Shape Analysis ◽  
Ct Scans ◽  
Lung Nodules ◽  
Automated Segmentation ◽  
Local Shape

Face spoofing detection from single images using texture and local shape analysis

2012 ◽  
Vol 1 (1) ◽  
pp. 3 ◽  
Author(s):  
J. Määttä ◽  
A. Hadid ◽  
M. Pietikäinen
Keyword(s):  
Shape Analysis ◽  
Local Shape ◽  
Spoofing Detection ◽  
Face Spoofing

scholarly journals New likelihoods for shape analysis

2015 ◽  
Vol 30 (09) ◽  
pp. 1550039 ◽  
Author(s):  
Sylvain Fichet
Keyword(s):  
Monte Carlo ◽  
Shape Analysis ◽  
Likelihood Function ◽  
Statistical Tests ◽  
Data Distribution ◽  
High Energy ◽  
Multivariate Case ◽  
The Moment ◽  
Signal Search ◽  
Energy Signal

We introduce a new kind of likelihood function based on the sequence of moments of the data distribution. Both binned and unbinned data samples are discussed, and the multivariate case is also derived. Building on this approach we lay out the formalism of shape analysis for signal searches. In addition to moment-based likelihoods, standard likelihoods and approximate statistical tests are provided. Enough material is included to make the paper self-contained from the perspective of shape analysis. We argue that the moment-based likelihoods can advantageously replace unbinned standard likelihoods for the search of nonlocal signals, by avoiding the step of fitting Monte Carlo generated distributions. This benefit increases with the number of variables simultaneously analyzed. The moment-based signal search is exemplified and tested in various 1D toy models mimicking typical high-energy signal-background configurations. Moment-based techniques should be particularly appropriate for the searches for effective operators at the LHC.

scholarly journals Local Shape Analysis using MANCOVA

2009 ◽  
Author(s):  
Beatriz Paniagua ◽  
Martin Styner ◽  
Marc Macenko ◽  
Dimitrios Pantazis ◽  
Marc Niethammer
Keyword(s):  
Statistical Analysis ◽  
Shape Analysis ◽  
Anatomical Structures ◽  
Local Shape ◽  
Independent Variables ◽  
Different Types ◽  
Statistical Shape ◽  
Localized Analysis ◽  
Associated Variables ◽  
Unified Method

Gross shape measures such as volume have been widely used in statistical analysis of anatomical structures. Statistical shape analysis methods have emerged within the last decade to allow for a localized analysis of shape. Most shape analysis frameworks are though lacking a good statistical underpinning, as they commonly do not allow for the inclusion of independent variables such as age, gender or clinical scores. This work presents a unified method for local shape analysis that can accomodate different number of variates and contrasts. It also allows to include any number of associated variables in the statistical analysis of the data. Several cases of study are given to clarify the explanation of the different types of data that can be analyzed and the parameters that can be used to tune the program shapeAnalysisMANCOVA. This tool has been designed to interact seamlessly with the existing UNC SPHARM-PDM based shape analysis toolbox.

scholarly journals Local Shape Analysis of the Hippocampus using Hierarchical Level-of-Detail Representations

2004 ◽  
Vol 11A (7) ◽  
pp. 555-562
Author(s):  
Jeong-Sik Kim ◽  
Soo-Mi Choi ◽  
Yoo-Ju Choi ◽  
Myoung-Hee Kim
Keyword(s):  
Shape Analysis ◽  
Level Of Detail ◽  
Hierarchical Level ◽  
Local Shape

Local Shape Analysis for Overlaid Data Structures

2013 ◽  
pp. 150-171 ◽  
Author(s):  
Cezara Drăgoi ◽  
Constantin Enea ◽  
Mihaela Sighireanu
Keyword(s):  
Data Structures ◽  
Shape Analysis ◽  
Local Shape
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