基于稀疏性和连续性的解卷提高了超声波图像的质量
Xiangyu Li1, Xin Zhang1, Chaolin Fan1
1Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China.
Computers in biology and medicine
|December 30, 2023
概括
这项研究引入了基于稀疏性和连续性 (DBSC) 的解卷算法,以增强超声波 (US) 成像. DBSC方法显著提高了图像分辨率,信号噪声比 (SNR) 和对比度,即使在硬件有限的设备中也是如此.
科学领域:
- 医疗成像医学成像
- 信号处理 信号处理
- 生物医学工程 生物医学工程
背景情况:
- 超声波 (US) 影像受限于低分辨率,斑点噪音,杂乱和文物.
- 现有的硬件和算法改进仍然需要增强分辨率,信号噪声比 (SNR) 和对比度.
- 美国小型设备面临硬件限制,加剧了这些局限性.
研究的目的:
- 提出一种基于稀疏性和连续性 (DBSC) 的新型解卷算法,以获得卓越的超声波图像质量.
- 为了解决超声波成像中的分辨率,SNR和对比度的局限性.
- 为了验证算法的有效性对具有限制硬件的设备.
主要方法:
- 采用了解卷算法,利用超声图像的稀疏性和连续性特性.
- 使用初始维纳过来提高分辨率,然后根据像素连续性和稀疏性进行噪声抑制.
- 使用相对稀疏度进行平衡的高频信息提取.
主要成果:
- DBSC算法在图像分辨率,对比度和SNR方面显示出显著的改进.
- 在超声波图像中证明了稀疏性和连续性属性的一般适用性.
- 通过不同传输通道的模拟,实验和调查验证了该方法的有效性.
结论:
- DBSC算法有效地提高了超声波图像分辨率,对比度和SNR.
- 拟议的方法适用于具有有限硬件能力的超声波设备上的应用.
- 稀疏性和连续性被确定为超声波图像增强的关键一般性质.
相关概念视频
Ultrasonography
4.5K
Ultrasonography is an imaging technique that uses high-frequency sound waves to visualize the body's internal structures. It is a non-invasive and safe procedure that does not involve the use of ionizing radiation, making it widely used in various medical fields. Ultrasonography is used to study heart function, blood flow in the neck or extremities, certain conditions such as gallbladder disease, and fetal growth and development.
During an ultrasonography procedure, a handheld device called...
During an ultrasonography procedure, a handheld device called...
4.5K
Deconvolution
162
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
162
Reconstruction of Signal using Interpolation
203
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
203
Convergence of Fourier Series
148
The Fourier series is a powerful mathematical tool for representing periodic signals as an infinite sum of complex exponentials. In practice, this infinite series is truncated to a finite number of terms, yielding a partial sum. This truncation makes the approximation of the signal feasible but introduces certain challenges, particularly near discontinuities, known as the Gibbs phenomenon.
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
The Gibbs phenomenon refers to the persistent oscillations and overshoots that occur near discontinuities...
148
Continuous -time Fourier Transform
318
The Fourier series is instrumental in representing periodic functions, offering a powerful method to decompose such functions into a sum of sinusoids. This technique, however, necessitates modification when applied to nonperiodic functions. Consider a pulse-train waveform consisting of a series of rectangular pulses. When these pulses have a finite period, they can be accurately represented by a Fourier series. Yet, as the period approaches infinity, resulting in a single, isolated pulse, the...
318


