DocumentCode :
2501495
Title :
Automatic segmentation of digital images applied in cardiac medical images
Author :
Peres, F.A. ; Oliveira, F.R. ; Neves, L.A. ; Godoy, M.F.
Author_Institution :
Fac. de Tecnol. de Sao Jose do Rio Preto, São José do Rio Preto, Brazil
fYear :
2010
fDate :
15-19 March 2010
Firstpage :
38
Lastpage :
42
Abstract :
The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature.
Keywords :
cardiology; feature extraction; image segmentation; maximum entropy methods; medical image processing; muscle; adaptable segmentation method; automatic multilevel thresholding; automatic segmentation; cardiac medical images; cardiac transplant; digital image processing; feature extraction; group histogram quantization; histogram slope; maximum entropy; myocardial images; Biomedical imaging; Biopsy; Digital images; Entropy; Feature extraction; Histograms; Image resolution; Image segmentation; Myocardium; Quantization; cardiac Imagens; segmentation; thresholding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Health Care Exchange (PAHCE), 2010 Pan American
Conference_Location :
Lima
Print_ISBN :
978-1-4244-6291-9
Type :
conf
DOI :
10.1109/PAHCE.2010.5474606
Filename :
5474606
Link To Document :
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