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Graph-based simulated annealing: a hybrid approach to stochastic modeling of complex microstructures

O Stenzel, D Westhoff, I Manke, M Kasper, D P Kroese, V Schmidt
2013 Modelling and Simulation in Materials Science and Engineering  
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

M Sreeteish
2022 International Journal for Research in Applied Science and Engineering Technology  
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

Yamini Upadhyay .
2014 International Journal of Research in Engineering and Technology  
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

Ralf Thiedmann, Ole Stenzel, Aaron Spettl, Paul R. Shearing, Stephen J. Harris, Nigel P. Brandon, Volker Schmidt
2011 Computational materials science  
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

Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida, Mohamed Benjelloun
2009 Zenodo  
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

Yue Wang, T. Adah, Jianhua Xuan, Z. Szabo
2001 IEEE Transactions on Information Technology in Biomedicine  
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

Gerd Gaiselmann, Ralf Thiedmann, Ingo Manke, Werner Lehnert, Volker Schmidt
2012 Computational materials science  
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

Dipak KumarKole, Amiya Halder
2012 International Journal of Computer Applications  
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]

Pasquale Coscia, Francesco A.N. Palmieri, Francesco Castaldo, Alberto Cavallo
2016 arXiv   pre-print
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

Ben T. Grys, Dara S. Lo, Nil Sahin, Oren Z. Kraus, Quaid Morris, Charles Boone, Brenda J. Andrews
2016 Journal of Cell Biology  
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

Lionel Benoit, Mathieu Vrac, Gregoire Mariethoz
2018 Hydrology and Earth System Sciences Discussions  
<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

Koon-Pong Wong, Dagan Feng, S.R. Meikle, M.J. Fulham
2002 IEEE Transactions on Nuclear Science  
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

Gerd Gaiselmann, Ingo Manke, Werner Lehnert, Volker Schmidt
2013 Image Analysis and Stereology  
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

Oeslle Lucena, Pedro Borges, Jorge Cardoso, Keyoumars Ashkan, Rachel Sparks, Sebastien Ourselin
2022 Frontiers in Radiology  
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

Anca Cristea, Jeroen Van Houtte, Anthony Paul Doulgeris
2020 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
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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