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Graph-based simulated annealing: a hybrid approach to stochastic modeling of complex microstructures
2013
Modelling and Simulation in Materials Science and Engineering
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As an example of application, the model is fitted to a tomographic image describing the microstructure of electrodes in Liion batteries. ...
P. and Schmidt, V. (2013) Graph-based simulated annealing: a hybrid approach to stochastic modeling of complex microstructures. ...
Description of material and imaging technique As an example of application, we fitted the stochastic simulation model proposed in the present paper to 3D image data that describe the microstructure of ...
doi:10.1088/0965-0393/21/5/055004
fatcat:gcqej2cla5huxjmp6lqmwbfn6u
Image De-Noising Using Convolutional Variational Autoencoders
2022
International Journal for Research in Applied Science and Engineering Technology
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Basic Autoencoder, Variational Autoencoder, and Convolutional Autoencoder are the three approaches that were employed to denoise the picture. ...
The autoencoder tries to figure out non-linear correlations between data points. An encoder, a latent space, and a decoder all exist in autoencoders. ...
The population-based image optimization technique with novel fitness functions is the emphasis of this portion of the image. ...
doi:10.22214/ijraset.2022.44826
fatcat:tb6ph7yiwbge7mlyf22cl3kzne
APPLICATION OF GENETIC ALGORITHM FOR LIVER CANCER DETECTION
2014
International Journal of Research in Engineering and Technology
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A better system has to be find for the segmentation of liver from MRI images so that it can be identified clearly from the adjacent organs which have similar intensity. ...
In this paper we will present different techniques for segmentation and will design a method for liver segmentation and cancer detection. ...
After which the valid and best fitted genes in chromosomes are mutated with a probability µc 7. ...
doi:10.15623/ijret.2014.0305051
fatcat:e64gotepurgrxaiioozbot5da4
Stochastic simulation model for the 3D morphology of composite materials in Li–ion batteries
2011
Computational materials science
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For this purpose, a statistical technique to fit the model to 3D image data gained by X-ray tomography is developed. ...
Finally, we validate the model by comparing real and simulated data using image characteristics which are especially relevant with respect to transport properties. ...
In Section 4 the modeling approach including a technique for model fitting is explained, whereas Section 5 deals with the validation of the stochastic simulation model by means of structural image characteristics ...
doi:10.1016/j.commatsci.2011.06.031
fatcat:lmcfzuhgl5hdpfpzdxzfbwcf6i
An Optimal Unsupervised Satellite Image Segmentation Approach Based On Pearson System And K-Means Clustering Algorithm Initialization
2009
Zenodo
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Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. ...
This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. ...
There has been recently considerable interest in stochastic model-based image segmentation techniques because of their efficiency. ...
doi:10.5281/zenodo.1085478
fatcat:d7fp2yxqcrd7vkfbkqvq3d622m
Magnetic resonance image analysis by information theoretic criteria and stochastic site models
2001
IEEE Transactions on Information Technology in Biomedicine
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We demonstrate the successful applications of the approach with synthetic data sets and then with real MR brain images. ...
Index Terms-Finite normal mixture, image segmentation, information theoretic criteria, patient site model, tissue quantification. ...
IMAGE MODELING In order to validate the use of a suitable stochastic model for MR image analysis with a specified objective, we have studied MR imaging statistics and observed several useful statistical ...
doi:10.1109/4233.924805
pmid:11420993
fatcat:ozeae5ihevd7thjmlzajimfy3q
Stochastic 3D modeling of fiber-based materials
2012
Computational materials science
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Exemplarily, on the basis of 2D data from SEM images, the parameters of the multi-layer model are fitted to the microstructure of a non-woven material which is used for gas-diffusion layers in PEM fuel ...
This fully parametrized model is based on ideas from stochastic geometry and multivariate time series analysis. ...
Recently, several approaches to stochastic modeling of fiber-based materials have been studied in the literature, see e.g. [1, 10, 16, 17, 19, 21] . ...
doi:10.1016/j.commatsci.2012.02.038
fatcat:yu2j2yps2zdhdj6djov5qtn75y
Automatic Brain Tumor Detection and Isolation of Tumor Cells from MRI Images
2012
International Journal of Computer Applications
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This paper proposes automatic brain tumor detection and isolation of tumor cells from MRI images using a genetic algorithm (GA) based clustering method, intensity based asymmetric map and region growing ...
Automatic Brain Tumor Detection refers to the problem of delineating tumorous tissues from MRI images for the purpose of medical diagnosis and surgical planning. ...
A Genetic Algorithm based clustering technique is used for this approach which is discussed in section 4. ...
doi:10.5120/4905-7416
fatcat:fmal3jayynfwfpgzy4qsyf2uqa
3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching
[article]
2016
arXiv
pre-print
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The pose estimation is obtained by applying a modified version of the Iterative Closest Point (ICP) algorithm to synthetic models to obtain the rigid transformation that aligns each model with respect ...
We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor. ...
Several approaches have also been proposed to estimate the hand pose from depth images. Mo et al. [12] use a laser-based camera to produce low-resolution depth images. ...
arXiv:1604.02032v1
fatcat:wkhw74hco5hh7f6hnl3rkxo2nq
Machine learning and computer vision approaches for phenotypic profiling
2016
Journal of Cell Biology
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To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering ...
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. ...
Imaging work in the Andrews and Boone labs is supported by foundation grants from the Canadian Institutes of Health Research. ...
doi:10.1083/jcb.201610026
pmid:27940887
pmcid:PMC5223612
fatcat:q4edewl4lndivg7gj4sucr7qze
Dealing with non-stationarity in sub-daily stochastic rainfall models
2018
Hydrology and Earth System Sciences Discussions
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<br><br> Our method is particularly suited to deal with non-stationarity in the context of sub-daily stochastic rainfall models. ...
To this end, we propose a methodology that automatically identifies rain types with homogeneous statistics. ...
Stochastic rainfall model The validation of the rain typing approach uses a stochastic rainfall model designed for local-scale (a few square kilometer extent) and high-resolution (up to 1 min) data. ...
doi:10.5194/hess-2018-273
fatcat:gv4oreeq6zcklhswcf2wgsfhpe
Segmentation of dynamic PET images using cluster analysis
2002
IEEE Transactions on Nuclear Science
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In this work, we describe an approach to automatically segment dynamic PET images using cluster analysis and we validate our approach with a simulated phantom study and assess its performance with real ...
Our preliminary results suggest that cluster analysis can automatically segment tissues in dynamic PET studies and has the potential to replace manual ROI delineation for some applications. ...
In this study, a model-based approach was adopted to cluster validation based on two information-theoretic criteria, namely, Akaike information criterion (AIC) [21] and Schwarz criterion (SC) [22] , ...
doi:10.1109/tns.2002.998752
fatcat:wv6vhtic5rcq7jqnojpyg54lge
EXTRACTION OF CURVED FIBERS FROM 3D DATA
2013
Image Analysis and Stereology
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Thus, in a second step, we consider a stochastic algorithm to adequately connect these parts of center lines to each other, with the general aim to reconstruct the complete fibers such that the curvature ...
The quality of the segmentation algorithm is validated by applying it to simulated test data. ...
Then, a technique to fit the parameters of the segmentation algorithm and to validate the quality of segmentation is briefly explained. A final section summarizes the results. ...
doi:10.5566/ias.v32.p57-63
fatcat:5iqpngctknbxbmuf2mk7jnkdpm
Informative and Reliable Tract Segmentation for Preoperative Planning
2022
Frontiers in Radiology
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We use a volume-based calibration approach to compute representative predicted probabilities from the estimated uncertainties. ...
We use a 3D U-Net to segment white matter tracts. We then estimate model and data uncertainty using test time dropout and test time augmentation, respectively. ...
TractSeg (10) , a voxel-based approach, uses 2D U-Nets (20) , in a tri-planar approach, to segment 72 tracts. ...
doi:10.3389/fradi.2022.866974
fatcat:bqrh3oxsnrbhheja325hdhxpny
Integrating Incidence Angle Dependencies into the Clustering-Based Segmentation of SAR Images
2020
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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The model simplicity also allows for short execution times and presents the segmentation approach as a potential operational algorithm. ...
We propose to integrate the target-specific intensity decay rates into a nonstationary statistical model, for use in a fully automatic and unsupervised segmentation algorithm. ...
The authors also wish to extend special thanks to their colleagues Malin Johansson, Thomas Kraemer, Johannes Lohse, and Wolfgang Dierking for offering their scientific and technical expertise. ...
doi:10.1109/jstars.2020.2993067
fatcat:npjblsemwfb4pffeku7w5frnxq
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