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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  3/2013 - 14

 HIGH-IMPACT PAPER 

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: 2,566 | Views: 2,232

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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