Automatic textural feature selection on echocardiographic images

Irene P. Ponce García; Raquel Valdés-Cristerna

doi:10.1117/12.652765

20 March 2006 Automatic textural feature selection on echocardiographic images

Irene P. Ponce García, Raquel Valdés-Cristerna

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61446Y (2006) https://doi.org/10.1117/12.652765
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

The quality of the information contents in echocardiographic images is often reduced by the presence of dropout, speckle, movement artifact, and far field attenuation, although ultrasound is suitable to assessing the dynamic aspect of heart. The aim of this work is to find a set of texture features that optimally characterize the cardiac chambers from echocardiographic images and to use the to segment the image. In this work, seventy-seven texture characteristics from echographic and borders map images were extracted. An optimal subset of them was selected by an automatic process based on a separateness criterion, classification rate criterion and sequential forward algorithm. As a result the optimal set of texture characteristics found was: {Echo, Homogeneity of the co-ocurrence matrix at 90°, Central moment 22 of original image and Central moment 22 of borders map}. The classification rate reached was of 76.4%.

Citation Download Citation

Irene P. Ponce García and Raquel Valdés-Cristerna "Automatic textural feature selection on echocardiographic images", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61446Y (20 March 2006); https://doi.org/10.1117/12.652765

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