Automatic textural feature selection on echocardiographic images

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%.