Abstract
Accurate estimation of ultrasound Doppler spectrogram envelope is essential for clinical pathological diagnosis of various cardiovascular diseases. However, due to intrinsic spectral broadening in the power spectrum and speckle noise existing in ultrasound images, it is difficult to obtain the accurate maximum velocity. Each of the standard existing methods has their own limitations and does not work well in complicated recordings. This paper proposes a robust automatic spectral envelope estimation method that is more accurate in phantom recordings and various in-vivo recordings than the currently used methods. Comparisons were performed on phantom recordings of the carotid artery with varying noise and additional in-vivo recordings. The accuracy of the proposed method was on average 8% greater than the existing methods. The experimental results demonstrate the wide applicability under different blood conditions and the robustness of the proposed algorithm.
Highlights
Ultrasonography is widely used in clinical diagnosis due to its low cost, non-invasive nature, real-time imaging capability and the gradual increase of image quality
This paper proposes a robust automatic spectral envelope estimation based on ultrasound Doppler blood flow spectrograms.The quadratic iteration algorithm (QIA) methods was tested on phantom recordings to show the accuracy of the QIA
The QIA method was tested on an ultrasound image of carotid artery with several levels of noise
Summary
Ultrasonography is widely used in clinical diagnosis due to its low cost, non-invasive nature, real-time imaging capability and the gradual increase of image quality. Noise existing in ultrasound images makes clinical diagnosis difficult. Maximum velocity and minimum velocity, respectively, correspond to the maximum velocity envelope and the minimum velocity envelope Both maximum velocity and minimum velocity envelope are often used in a quantity of clinical diagnostic applications. Blood flow volume assessment, which is calculated by the maximum velocity of blood and the vessel area, can be used in a number of clinical applications [3] such as cerebral blood flow assessment [4], arteriovenous fistula inspection [5], anesthesia [6] and fetal outcome assessment [7]. With the increasing use of ultrasonography in clinical diagnosis, a more effective and automatic method needs to be proposed to reduce the work of doctor and to allow easier use by undertrained or untrained users
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