Abstract
Ultrasound is currently widely used in clinical diagnosis because of its fast and safe imaging principles. As the anatomical structures present in an ultrasound image are not as clear as CT or MRI. Physicians usually need advance clinical knowledge and experience to distinguish diseased tissues. Fast simulation of ultrasound provides a cost-effective way for the training and correlation of ultrasound and the anatomic structures. In this paper, a novel method is proposed for fast simulation of ultrasound from a CT image. A multiscale method is developed to enhance tubular structures so as to simulate the blood flow. The acoustic response of common tissues is generated by weighted integration of adjacent regions on the ultrasound propagation path in the CT image, from which parameters, including attenuation, reflection, scattering, and noise, are estimated simultaneously. The thin-plate spline interpolation method is employed to transform the simulation image between polar and rectangular coordinate systems. The Kaiser window function is utilized to produce integration and radial blurring effects of multiple transducer elements. Experimental results show that the developed method is very fast and effective, allowing realistic ultrasound to be fast generated. Given that the developed method is fully automatic, it can be utilized for ultrasound guided navigation in clinical practice and for training purpose.
Highlights
The imaging principle behind an ultrasound is that the ultrasound wave generates a different amount of reflection or refraction when accounting for different tissues inside the human body
The parameters of acoustic response are based on the intensity difference ratio of adjacent regions for acoustic wave propagation in a piecewise homogenous medium and are fast calculated
The detected edge information on different tissues is combined with random noises to simulate the acoustic response rate of the interesting region
Summary
The imaging principle behind an ultrasound is that the ultrasound wave generates a different amount of reflection or refraction when accounting for different tissues inside the human body. The displayed 2D echocardiographic image is defined and controlled by the orientation of the virtual scan plane Such a simulation method requires the 3D ultrasound volume data to be acquired in advance, guaranteeing good image quality and high-speed scanning of the image slice. Based on the method of Shams, Kutter et al [11] used a ray-based model combined with speckle patterns derived from a preprocessed CT image to generate view-dependent ultrasonic effects, such as occlusions, large-scale reflections, and attenuation. In his method, Graphics Processing Unit (GPU) was introduced for speed acceleration. As the response coefficient of ultrasound is calculated by the intensity differences of adjacent regions in the ultrasound propagation path, the complexity of the simulation procedure is greatly reduced
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