Abstract
In echo-cardiac clinical computer-aided diagnosis, an important step is to automatically classify echocardiography videos from different angles and different regions. We propose a kind of echocardiography video classification algorithm based on the dense trajectory and difference histograms of oriented gradients (DHOG). First, we use the dense grid method to describe feature characteristics in each frame of echocardiography sequence and then track these feature points by applying the dense optical flow. In order to overcome the influence of the rapid and irregular movement of echocardiography videos and get more robust tracking results, we also design a trajectory description algorithm which uses the derivative of the optical flow to obtain the motion trajectory information and associates the different characteristics (e.g., the trajectory shape, DHOG, HOF, and MBH) with embedded structural information of the spatiotemporal pyramid. To avoid “dimension disaster,” we apply Fisher's vector to reduce the dimension of feature description followed by the SVM linear classifier to improve the final classification result. The average accuracy of echocardiography video classification is 77.12% for all eight viewpoints and 100% for three primary viewpoints.
Highlights
The echocardiography video still plays an important role in modern medical diagnosis
We propose a method based on the dense trajectory [11] and difference histograms of oriented gradients (DHOG)
In order to describe the dense trajectory, this paper proposes a method based on motion boundaries and structure descriptors (DHOG, histograms of optical flow (HOF), and motion boundary histograms (MBH)), which has the better result
Summary
The echocardiography video still plays an important role in modern medical diagnosis. The echocardiography video gets the 3D detailed anatomical structure and functional information of the heart from eight standard views, which are usually taken from an ultrasound transducer at the three primary positions (Apical Angles (AA), Parasternal Long Axis (PLA), and Parasternal Short Axis (PSA)). Because of the ultrasound characteristic limits, such as the high noise caused by the low contrast ratio in echocardiography video, sonographer has to manually classify these echocardiography videos. It causes the great decrease of working efficiency and impacts the recognition results owing to sonographer experience and image resolution. How to use the computer to classify the echocardiography video is a crucial step in the current echocardiac research
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