Edge-detection and segmentation methods for two-dimensional echocardiograms
The purpose of this Edge Detection and Segmentation Method for Two-Dimensional Echocardiogram is to present the procedures to detect and segment an image from Two-Dimensional Echocardiogram and to generate a scanline that can be used to detect the distance between two endocardiums which is useful to...
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| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2014
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| Online Access: | http://www.scopus.com/inward/record.url?eid=2-s2.0-28144449964&partnerID=40&md5=843e1193c31ad4d14a0472c0e643c9fa http://cmuir.cmu.ac.th/handle/6653943832/4392 |
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| Institution: | Chiang Mai University |
| Language: | English |
| Summary: | The purpose of this Edge Detection and Segmentation Method for Two-Dimensional Echocardiogram is to present the procedures to detect and segment an image from Two-Dimensional Echocardiogram and to generate a scanline that can be used to detect the distance between two endocardiums which is useful to analyze heart disease. This method applies image processing and computer graphic algorithms which were divided into 3 steps. Firstly, we used image improvement algorithms of noise suppression, histogram, brightness adjustment, threshold and median filtering. Then, Edge Detection algorithm with sobel compass gradient mask was applied to show the edge of endocardium border. Finally, segmentation and some computer graphics algorithms were used to identify and generate contour line of the endocardium border. Later in the study, Pearson correlation coefficient was used to evaluate performance of this method compared with that of manual track. The average correlation computes from this method is 0.9 which shows a good result because 0.9 is very close to 1. However, some part of contour line has a big error value. The unexpected result from incomplete of endocardium border came from color value of some part of border very close to background or noise color value. This problem occurred in first step can be solved by carefully collecting in collection process. © 2004 IEEE. |
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