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Multimodality Image Registration Using an Extensible Information Metric and High Dimensional Histogramming [chapter]

Jie Zhang, Anand Rangarajan
2005 Lecture Notes in Computer Science  
Our results demonstrate the efficacy of the metrics and high-dimensional histogramming in affine, multimodality image registration.  ...  To showcase the new measure, we compare the results of direct multimodality registration using high-dimensional histogramming with repeated intermodality registration.  ...  Mutual information of multiple random variables [5] is not necessarily nonnegative, which renders it inadequate as an image similarity measure.  ... 
doi:10.1007/11505730_60 fatcat:so7vxwzwcjbqhbznpqzvoao23y

Who Will Follow Whom? Exploiting Semantics for Link Prediction in Attention-Information Networks [chapter]

Matthew Rowe, Milan Stankovic, Harith Alani
2012 Lecture Notes in Computer Science  
the presence of mutual nodes.  ...  This latter contribution exposes latent factors within social networks and the existence of a clear need for topical affinity between users for a follow link to be created.  ...  Mutual Followers Count. Measures the overlap of the follower sets (i.e. the set of users connecting into a given user) between u and v.  ... 
doi:10.1007/978-3-642-35176-1_30 fatcat:wdi7bsbbnveqxohukfhvnbmilm

Optimal state estimation for stochastic systems: an information theoretic approach

Xiangbo Feng, K.A. Loparo, Yuguang Fang
1997 IEEE Transactions on Automatic Control  
It is shown that for a linear stochastic system with an affine linear filter for the homogeneous system, under some reachability and observability conditions, zero mutual information between estimation  ...  In this paper, we examine the problem of optimal state estimation or filtering in stochastic systems using an approach based on information theoretic measures.  ...  Another important concept is the mutual information of , which is defined as (3) Roughly speaking, the differential entropy measures the dispersion of the random variable .  ... 
doi:10.1109/9.587329 fatcat:5opf47dg5nb3tcidjadsg23vee

A Hybrid System for Survival Analysis after EVAR Treatment of AAA [chapter]

Josu Maiora, Manuel Graña
2011 Lecture Notes in Computer Science  
Previously published methods measure the deformation of the aorta between two studies of the same patient using image registration techniques.  ...  The features used for classification are the volume registration quality measures after each of the image registration steps. This system provides the medical team an additional decision support tool.  ...  The feature vectors consist of the similarity measures computed on the segmented lumen after rigid, affine and deformable registration.  ... 
doi:10.1007/978-3-642-21222-2_42 fatcat:xi3dzqxhlbdk3fo4qttycy2jia

Information Geometry of Randomized Quantum State Tomography

Akio Fujiwara, Koichi Yamagata
2018 Entropy  
) | for a = 1 , ⋯ , d + 1 , where the numbers of applications of these measurements are random variables.  ...  We show that the space of the resulting probability distributions enjoys a mutually orthogonal dualistic foliation structure, which provides us with a simple geometrical insight into the maximum likelihood  ...  Geometry of Randomized State Tomography We identify the randomized state tomography on H C d with the following scheme [21] : at each step of the measurement, one chooses a PVM M (a) at random with probability  ... 
doi:10.3390/e20080609 pmid:33265698 fatcat:r7tlrowndjbuxgib6kwttfmq64

Efficient Stochastic Gradient Search for Automatic Image Registration

Q. Li
2007 International Journal of Simulation Modelling  
The main contribution of this paper is the first accomplishment of an efficient stochastic gradient search strategy on the mutual information based automatic image registration.  ...  The registration experiments are associated with the pairs of optical sensor images, synthetic aperture radar images and medical multimodality images, which are misaligned by the rigid or affine transformations  ...  Mutual information Based on the information theory [9] , the definition of standard mutual information, MI(A,B), of two random signals A and B can be calculated as follows: ) , ( ) ( ) ( ) , ( B A H B  ... 
doi:10.2507/ijsimm06(2)s.06 fatcat:5uwnkzpagzhf3jzu4hh2ynqoci

Multi-modal Medical Image Registration by Local Affine Transformations

Liliana Lo Presti, Marco La Cascia
2018 Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods  
This paper proposes to register a pair of images by iteratively maximizing the empirical mutual information through coordinate gradient descent.  ...  Hence, the registered image is obtained by applying a sequence of local affine transformations.  ...  EMPIRICAL MUTUAL INFORMATION Entropy H(X) is a measure derived by information theory that allows us to quantify the randomness of a random variable X, and is defined as follows: H(X) = − ∑ ∀x p(X = x)  ... 
doi:10.5220/0006656405340540 dblp:conf/icpram/PrestiC18 fatcat:aapkfjcrwjdkhmm5yg2qb26rpy

Message Passing in Clusters using Fuzzy Density based Clustering

M. Suganya, S. Nagarajan
2015 Indian Journal of Science and Technology  
In Fuzzy DENCLUE, number of clusters is reduced and randomness in the form of noise is removed. The experiment is performed in Net Beans 8.0.2 using jdk1.7 as a language.  ...  A dynamic variant of AP clustering called Incremental Affinity Propagation with K-Medoid (IAPKM) is used along with the Fuzzy Density based clustering (DENCLUE) method.  ...  sum of Similarities measures the similarity between objects and its nearest exemplar. i is the object and c i is the nearest exemplar.Normalized Mutual information computes the mutual information between  ... 
doi:10.17485/ijst/2015/v8i16/61761 fatcat:olkjmvxb6fgtvchtasaiut2ule

Maximal Information Leakage based Privacy Preserving Data Disclosure Mechanisms [article]

Tianrui Xiao, Ashish Khisti
2019 arXiv   pre-print
We show that the optimal solution is the same as the case when the utility is measured using probability of error at the adversary.  ...  We then consider an application of this framework to a data driven setting and provide an empirical approximation to the Sibson mutual information.  ...  ACKNOWLEDGMENT The authors would like to thank Vincent Y.F. Tan for his insights and advice in the course of developing this work.  ... 
arXiv:1904.01147v2 fatcat:omkteem2qbgxznq6fsty47ftsu

A Fully Automated Method for Discovering Community Structures in High Dimensional Data

Jianhua Ruan
2009 2009 Ninth IEEE International Conference on Data Mining  
The advantage of this type of approaches is that the algorithm does not require any parameter to be tuned.  ...  Furthermore, our method can suggest appropriate preprocessing / normalization of the data to improve the results of community identification.  ...  Given the distance measure, we construct a mutual kNN graph [17] .  ... 
doi:10.1109/icdm.2009.141 pmid:25296858 pmcid:PMC4185921 dblp:conf/icdm/Ruan09 fatcat:em5olwtcibebrigg7ckusxdeom

Affine Masking against Higher-Order Side Channel Analysis [chapter]

Guillaume Fumaroli, Ange Martinelli, Emmanuel Prouff, Matthieu Rivain
2011 Lecture Notes in Computer Science  
A common countermeasure for implementations of block ciphers is Boolean masking which randomizes the variables to be protected by the bitwise addition of one or several random value(s).  ...  We show how to apply it to AES at the cost of a small timing overhead compared to Boolean masking. We then conduct an in-depth analysis pinpointing the leakage reduction implied by affine masking.  ...  N bool ) the number of leakage measurements for a successful attack on affine masking (resp. Boolean masking).  ... 
doi:10.1007/978-3-642-19574-7_18 fatcat:puaqrbogunfslfqlh57oqlqlk4

Robust Image Registration Based on Mutual Information Measure

Witold Kosiński, Paweł Michalak, Piotr Gut
2012 Journal of Signal and Information Processing  
The registration is achieved if the maximum of the mutual information is attained. In this maximization process optimal values of five parameters of an affine transformation are searched.  ...  A new implementation of the image registration algorithm based on the mutual information is presented for the case of medical images.  ...  It measures statistical dependence of two random variables and presents how much information one random variable provides about another random variable.  ... 
doi:10.4236/jsip.2012.32023 fatcat:jwkil4e77febfakxtgpj3w354y

Overlapping Communities in Social Networks [article]

Jan Dreier and Philipp Kuinke and Rafael Przybylski and Felix Reidl and Peter Rossmanith and Somnath Sikdar
2014 arXiv   pre-print
In essence, given the community information of a small number of "seed nodes", the method uses random walks from the seed nodes to uncover the community information of the whole network.  ...  The algorithm runs in time O(k · m · n), where m is the number of edges; n the number of links; and k the number of communities in the network.  ...  The Shannon entropy of the partition A is defined as: H(A) = − A∈A n A n log 2 n A n . (11) The mutual information of two random variables is a measure of their mutual dependence.  ... 
arXiv:1412.4973v2 fatcat:uriho4tntvavnlkix4rt4x5nci

A graph-based approach to corner matching using mutual information as a local similarity measure

M.I.A. Lourakis, A.A. Argyros, K. Marias
2004 Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004.  
The common approach to dealing with this problem starts by ranking potential matches according to their affinity, which is assessed with the aid of window-based intensity similarity measures.  ...  This paper puts forward a novel approach for solving the corner matching problem that uses mutual information as a window similarity measure, combined with graph matching techniques for determining a matching  ...  Mutual Information Mutual information (MI) is an information theoretic similarity measure assessing the dependence of one random variable on another.  ... 
doi:10.1109/icpr.2004.1334386 dblp:conf/icpr/LourakisAM04 fatcat:to3y5lcp5rdrtlw42sx3nko3cm

Uncalibrated non-rigid factorisation with automatic shape basis selection

Sami S. Brandt, Pekka Koskenkorva, Juho Kannala, Anders Heyden
2009 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops  
The independent bases can be found by independent subspace analysis (ISA) which leads to the minimisation of mutual information between the basis shapes.  ...  To solve the remaining unknowns of the general affine transformation, we propose an iterative method that recovers the block structure of the factored motion matrix.  ...  Mutual Information Minimisation As the criterion for statistical independence, ICA can be defined as the minimisation of the mutual information of N scalar random variables X 1 , X 2 , . . . , X N , or  ... 
doi:10.1109/iccvw.2009.5457678 dblp:conf/iccvw/BrandtKKH09 fatcat:xveqydlqbzb4xalrsluw462im4
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