Application of texture analysis in echocardiography images for myocardial infarction tissue
Texture analysis is an important characteristic for surface and object identification from medical images and many other types of images. This research has developed an algorithm for texture analysis using medical images do trained from echocardiography in identifying heart with suspected myocard...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Penerbit UTM Press
2007
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| Subjects: | |
| Online Access: | http://eprints.utm.my/8044/3/SyedAbdulRahman2007_ApplicationofTextureAanalysisinEchocardiography.pdf http://eprints.utm.my/8044/4/285 |
| Summary: | Texture analysis is an important characteristic for surface and object identification from
medical images and many other types of images. This research has developed an algorithm for texture
analysis using medical images do trained from echocardiography in identifying heart with suspected
myocardial infarction problem. A set of combination of wavelet extension transform with gray level
co-occurrence matrix is proposed. In this work, wavelet extension transform is used to form an image
approximation with higher resolution. The gray level co-occurrence matrices computed for each subband
are used to extract four feature vectors: entropy, contrast, energy (angular second moment) and
homogeneity (inverse difference moment). The classifier used in this work is the Mahalanobis distance
classifier. The method is tested with clinical data from echocardiography images of 17 patients. For
each patient, tissue samples are taken from suspected infarcted area as well as from non-infarcted
(normal) area. For each patient, 8 frames separated by some time interval are used and for each frame,
5 normal regions and 5 suspected myocardial infarction regions of 16×16 pixel size are analyzed. The
classification performance achieved 91.32% accuracy. |
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