scholarly journals VOLUME ESTIMATION FROM SINGLE IMAGES: AN APPLICATION TO PANCREATIC ISLETS

2018 ◽  
Vol 37 (3) ◽  
pp. 191 ◽  
Author(s):  
Jiří Dvořák ◽  
Jan Švihlík ◽  
Jan Kybic ◽  
Barbora Radochová ◽  
Jiří Janáček ◽  
...  
Keyword(s):  
Volume Estimation ◽  
Estimation Methods ◽  
Particle Model ◽  
Shape Descriptors ◽  
Single Image ◽  
Simple Shape ◽  
Segmented Image ◽  
Image Volume ◽  
3D Shapes ◽  
Better Than

The present paper deals with the problem of volume estimation of individual objects from a single 2D view. Our main application is volume estimation of pancreatic (Langerhans) islets and the single 2D view constraint comes from the time and equipment limitations of the standard clinical procedure.Two main approaches are followed in this paper. First, two regression-based methods are proposed, using a set of simple shape descriptors of the segmented image of the islet. Second, two example-based methods are proposed, based on a database of islets with known volume. For training and evaluation, islet volumes were determined by OPT microscopy and a semi-automatical stereological volume estimation using the so-called Fakir probes.The performance of the single image volume estimation methods is studied on a set of 99 islets from human donors. Further experiments were also performed on a stone dataset and on synthetic 3D shapes, generated using a flexible stochastic particle model. The proposed methods are fast and the experimental results show that in most situations the proposed methods perform significantly better than the methods currently used in clinical practice, which are based on simple spherical or ellipsoidal models.

An Assessment of White Spruce Tree Volume Equations in Canada

1990 ◽  
Vol 66 (6) ◽  
pp. 600-605 ◽  
Author(s):  
R. T. Morton ◽  
T. I. Grabowski ◽  
S. J. Titus ◽  
G. M. Bonnor
Keyword(s):  
Goodness Of Fit ◽  
White Spruce ◽  
Volume Estimation ◽  
Estimation Methods ◽  
Single Model ◽  
Variable Model ◽  
Fit Statistics ◽  
Volume Equations ◽  
Better Than

In 1985, a survey of nine provinces and two territories was conducted to summarize operational tree volume estimation methods. Based on those results, six tree volume estimation functions were evaluated to answer the question: can a single model be used nation-wide for tree volume estimation? The six models were fitted to nation-wide data for 980 white spruce trees distributed nearly equally among the provinces and territories. Based on goodness of fit statistics and analysis of residuals, Schumacher's (1933) model and the Quebec combined variable model performed marginally better than the others. Further, the analyses did not reveal any significant differences between territories and provinces. It appears that any of these models could be applied to broad regions of Canada without suffering significant losses in accuracy.

Evaluation for estimating of the PDF and the CDF of Generalized Inverted Exponential Distribution with Application in Industry

2020 ◽  
pp. 507-522
Author(s):  
Parisa Torkaman
Keyword(s):  
Least Squares ◽  
Exponential Distribution ◽  
Mean Squared Error ◽  
Weighted Least Squares ◽  
Real Data ◽  
Minimum Variance ◽  
Cumulative Distribution ◽  
Estimation Methods ◽  
Data Set ◽  
Better Than

The generalized inverted exponential distribution is introduced as a lifetime model with good statistical properties. This paper, the estimation of the probability density function and the cumulative distribution function of with five different estimation methods: uniformly minimum variance unbiased(UMVU), maximum likelihood(ML), least squares(LS), weighted least squares (WLS) and percentile(PC) estimators are considered. The performance of these estimation procedures, based on the mean squared error (MSE) by numerical simulations are compared. Simulation studies express that the UMVU estimator performs better than others and when the sample size is large enough the ML and UMVU estimators are almost equivalent and efficient than LS, WLS and PC. Finally, the result using a real data set are analyzed.

scholarly journals Computational Geometry-Based Surface Reconstruction for Volume Estimation: A Case Study on Magnitude-Frequency Relations for a LiDAR-Derived Rockfall Inventory

2021 ◽  
Vol 10 (3) ◽  
pp. 157
Author(s):  
Paul-Mark DiFrancesco ◽  
David A. Bonneau ◽  
D. Jean Hutchinson
Keyword(s):  
Computational Geometry ◽  
Surface Reconstruction ◽  
Power Law ◽  
Point Cloud ◽  
Point Clouds ◽  
Volume Estimation ◽  
Estimation Methods ◽  
Small Scale ◽  
Reconstruction Methods ◽  
3D Volume

Key to the quantification of rockfall hazard is an understanding of its magnitude-frequency behaviour. Remote sensing has allowed for the accurate observation of rockfall activity, with methods being developed for digitally assembling the monitored occurrences into a rockfall database. A prevalent challenge is the quantification of rockfall volume, whilst fully considering the 3D information stored in each of the extracted rockfall point clouds. Surface reconstruction is utilized to construct a 3D digital surface representation, allowing for an estimation of the volume of space that a point cloud occupies. Given various point cloud imperfections, it is difficult for methods to generate digital surface representations of rockfall with detailed geometry and correct topology. In this study, we tested four different computational geometry-based surface reconstruction methods on a database comprised of 3668 rockfalls. The database was derived from a 5-year LiDAR monitoring campaign of an active rock slope in interior British Columbia, Canada. Each method resulted in a different magnitude-frequency distribution of rockfall. The implications of 3D volume estimation were demonstrated utilizing surface mesh visualization, cumulative magnitude-frequency plots, power-law fitting, and projected annual frequencies of rockfall occurrence. The 3D volume estimation methods caused a notable shift in the magnitude-frequency relations, while the power-law scaling parameters remained relatively similar. We determined that the optimal 3D volume calculation approach is a hybrid methodology comprised of the Power Crust reconstruction and the Alpha Solid reconstruction. The Alpha Solid approach is to be used on small-scale point clouds, characterized with high curvatures relative to their sampling density, which challenge the Power Crust sampling assumptions.

scholarly journals Real-Time Single Image Depth Perception in the Wild with Handheld Devices

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 15
Author(s):  
Filippo Aleotti ◽  
Giulio Zaccaroni ◽  
Luca Bartolomei ◽  
Matteo Poggi ◽  
Fabio Tosi ◽  
...  
Keyword(s):  
Real Time ◽  
Depth Perception ◽  
Depth Estimation ◽  
Autonomous Driving ◽  
Estimation Methods ◽  
Handheld Devices ◽  
Single Image ◽  
Handheld Device ◽  
Time Performance ◽  
In The Wild

Depth perception is paramount for tackling real-world problems, ranging from autonomous driving to consumer applications. For the latter, depth estimation from a single image would represent the most versatile solution since a standard camera is available on almost any handheld device. Nonetheless, two main issues limit the practical deployment of monocular depth estimation methods on such devices: (i) the low reliability when deployed in the wild and (ii) the resources needed to achieve real-time performance, often not compatible with low-power embedded systems. Therefore, in this paper, we deeply investigate all these issues, showing how they are both addressable by adopting appropriate network design and training strategies. Moreover, we also outline how to map the resulting networks on handheld devices to achieve real-time performance. Our thorough evaluation highlights the ability of such fast networks to generalize well to new environments, a crucial feature required to tackle the extremely varied contexts faced in real applications. Indeed, to further support this evidence, we report experimental results concerning real-time, depth-aware augmented reality and image blurring with smartphones in the wild.

scholarly journals Bayesian Uncertainty Estimation for Gaussian Graphical Models and Centrality Indices

2021 ◽  
Author(s):  
Joran Jongerling ◽  
Sacha Epskamp ◽  
Donald Ray Williams
Keyword(s):  
Bayesian Estimation ◽  
Graphical Models ◽  
Estimation Methods ◽  
Centrality Measures ◽  
Gaussian Graphical Models ◽  
Graphical Lasso ◽  
Study Results ◽  
Partial Correlations ◽  
Good Coverage ◽  
Better Than

Gaussian Graphical Models (GGMs) are often estimated using regularized estimation and the graphical LASSO (GLASSO). However, the GLASSO has difficulty estimating(uncertainty in) centrality indices of nodes. Regularized Bayesian estimation might provide a solution, as it is better suited to deal with bias in the sampling distribution ofcentrality indices. This study therefore compares estimation of GGMs with a Bayesian GLASSO- and a Horseshoe prior to estimation using the frequentist GLASSO in an extensive simulation study. Results showed that out of the two Bayesian estimation methods, the Bayesian GLASSO performed best. In addition, the Bayesian GLASSOperformed better than the frequentist GLASSO with respect to bias in edge weights, centrality measures, correlation between estimated and true partial correlations, andspecificity. With respect to sensitivity the frequentist GLASSO performs better.However, sensitivity of the Bayesian GLASSO is close to that of the frequentist GLASSO (except for the smallest N used in the simulations) and tends to be favored over the frequentist GLASSO in terms of F1. With respect to uncertainty in the centrality measures, the Bayesian GLASSO shows good coverage for strength andcloseness centrality. Uncertainty in betweenness centrality is estimated less well, and typically overestimated by the Bayesian GLASSO.

scholarly journals Glacier Volume Estimation on Cascade Volcanoes: An Analysis and Comparison with Other Methods

1986 ◽  
Vol 8 ◽  
pp. 59-64 ◽  
Author(s):  
C.L. Driedger ◽  
P.M. Kennard
Keyword(s):  
Estimation Method ◽  
Cascade Range ◽  
Volume Estimation ◽  
Aerial Photographs ◽  
Topographic Maps ◽  
Estimation Methods ◽  
Ice Thickness ◽  
Mount Rainier ◽  
Three Sisters ◽  
Mount St Helens

During the 1980 eruption of Mount St. Helens, the occurrence of floods and mudflows made apparent a need to assess mudflow hazards on other Cascade volcanoes. A basic requirement for such analysis is information about the volume and distribution of snow and ice on these volcanoes.An analysis was made of the volume-estimation methods developed by previous authors and a volume- estimation method was developed for use in the Cascade Range. A radio echo-sounder, carried in a backpack, was used to make point measurements of ice thickness on major glaciers of four Cascade volcanoes (Mount Rainier, Washington; Mount Hood and the Three Sisters, Oregon; and Mount Shasta, California), These data were used to generate ice-thickness maps and bedrock topographic maps for developing and testing volume-estimation methods. Subsequently, the methods were applied to the unmeasured glaciers on those mountains and, as a test of the geographical extent of applicability, to glaciers beyond the Cascades having measured volumes.Two empirical relationships were required in order to predict volumes for all the glaciers. Generally, for glaciers less than 2.6 km in length, volume was found to be estimated best by using glacier area, raised to a power. For longer glaciers, volume was found to be estimated best by using a power law relationship, including slope and shear stress. The necessary variables can be estimated from topographic maps and aerial photographs.

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