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A threshold selection method from gray level histograms
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This article is published in IEEE Transactions on Systems, Man, and Cybernetics.The article was published on 1979-01-01. It has received 37017 citations till now.read more
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Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
TL;DR: The authors propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations.
Journal ArticleDOI
A nonparametric method for automatic correction of intensity nonuniformity in MRI data
TL;DR: A novel approach to correcting for intensity nonuniformity in magnetic resonance (MR) data is described that achieves high performance without requiring a model of the tissue classes present, and is applied at an early stage in an automated data analysis, before a tissue model is available.
Journal ArticleDOI
Survey over image thresholding techniques and quantitative performance evaluation
Mehmet Sezgin,Bulent Sankur +1 more
TL;DR: 40 selected thresholding methods from various categories are compared in the context of nondestructive testing applications as well as for document images, and the thresholding algorithms that perform uniformly better over nonde- structive testing and document image applications are identified.
Journal ArticleDOI
Functional Demarcation of Active and Silent Chromatin Domains in Human HOX Loci by Noncoding RNAs
John L. Rinn,Michael Kertesz,Jordon K. Wang,Sharon L. Squazzo,Xiao Xu,Samantha A. Brugmann,L. Henry Goodnough,Jill A. Helms,Peggy J. Farnham,Eran Segal,Howard Y. Chang +10 more
TL;DR: The transcriptional landscape of the four human HOX loci is characterized at five base pair resolution in 11 anatomic sites and 231 HOX ncRNAs are identified that extend known transcribed regions by more than 30 kilobases, suggesting transcription of ncRNA may demarcate chromosomal domains of gene silencing at a distance.
Journal ArticleDOI
A new method for gray-level picture thresholding using the entropy of the histogram
TL;DR: Two methods of entropic thresholding proposed by Pun (Signal Process.,2, 1980, 223–237;Comput.16, 1981, 210–239) have been carefully and critically examined and a new method with a sound theoretical foundation is proposed.
References
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Journal ArticleDOI
The analysis of cell images.
TL;DR: A system with three basic components: 1) a sensor which rigorously and effectively scans microscopic fields and converts the optical information into digital form; 2) human analysts who contribute heuristics, devise image processing methods and 3) quantitative methods which fully utilize measurements of light intensity of optical density.
Journal ArticleDOI
Automatic boundary detection of the left ventricle from cineangiograms.
C.K. Chow,T. Kaneko +1 more
TL;DR: Experimental results on cardioangiograms are presented to successfully demonstrate the feasibility of the threshold method to detect boundaries in radiographic images, which is insensitive to shading or gradually varying interference.
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An Optimal Data Association Problem in Surveillance Theory
TL;DR: A method of inverse probability is obtained which permits maximum likelihood estimates to be made of the true data-surveillance object association and the maximum likelihood estimator is given in a form that lends itself to sequential computations performed in real time as the data arrives.
Journal ArticleDOI
A Threshold Selection Technique
TL;DR: A method of handling cases in which the peaks are very unequal in size and the valley is broad is described, in which points that lie on or near the edges of objects are determined.
Journal ArticleDOI
A branching algorithm for discriminating and tracking multiple objects
P. Smith,G. Buechler +1 more
TL;DR: A recursive branching algorithm for multiple-object discrimination and tracking consists of a bank of parallel filters of the Kalman form, each of which estimates a trajectory associated with a certain selected measurement sequence.