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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
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ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 644266260
doi: 10.4316/AECE


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  3/2013 - 14

A Comparison of X-Ray Image Segmentation Techniques

STOLOJESCU-CRISAN, C. See more information about STOLOJESCU-CRISAN, C. on SCOPUS See more information about STOLOJESCU-CRISAN, C. on IEEExplore See more information about STOLOJESCU-CRISAN, C. on Web of Science, HOLBAN, S. See more information about HOLBAN, S. on SCOPUS See more information about HOLBAN, S. on SCOPUS See more information about HOLBAN, S. on Web of Science
 
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Download PDF pdficon (722 KB) | Citation | Downloads: 1,260 | Views: 5,173

Author keywords
image processing, image segmentation, biomedical imaging, digital images, X-rays

References keywords
segmentation(30), image(30), images(11), medical(10), processing(9), analysis(7), techniques(6), automatic(6), active(6), technology(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2013-08-31
Volume 13, Issue 3, Year 2013, On page(s): 85 - 92
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2013.03014
Web of Science Accession Number: 000326321600014
SCOPUS ID: 84884928131

Abstract
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Image segmentation operation has a great importance in most medical imaging applications, by extracting anatomical structures from medical images. There are many image segmentation techniques available in the literature, each of them having advantages and disadvantages. The extraction of bone contours from X-ray images has received a considerable amount of attention in the literature recently, because they represent a vital step in the computer analysis of this kind of images. The aim of X-ray segmentation is to subdivide the image in various portions, so that it can help doctors during the study of the bone structure, for the detection of fractures in bones, or for planning the treatment before surgery. The goal of this paper is to review the most important image segmentation methods starting from a data base composed by real X-ray images. We will discuss the principle and the mathematical model for each method, highlighting the strengths and weaknesses.


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References Weight

Web of Science® Citations for all references: 4,795 TCR
SCOPUS® Citations for all references: 15,474 TCR

Web of Science® Average Citations per reference: 98 ACR
SCOPUS® Average Citations per reference: 316 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2016-12-09 10:42 in 134 seconds.




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