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虚拟源分布的多目标优化,用于超快的分离波成像
Zahraa Alzein1, Marco Crocco2, Daniele D Caviglia3
1Department of Electrical, Electronic, Telecommunications Engineering, and Naval Architecture (DITEN) University of Genoa, Genoa, 16145, Italy; Esaote S.p.A, Genova, 1645, Liguria, Italy.
Ultrasonics
|February 12, 2026
概括
使用遗传算法优化虚拟源 (VS) 在分离波成像 (DWI) 中的位置,显著提高了图像质量. 这种方法提高了分辨率和对比度,克服了超快超声波的视野限制.
科学领域:
- 超声波成像 超声波成像
- 医学物理 医学物理
- 计算机成像成像技术
背景情况:
- 分离波成像 (DWI) 使用虚拟源 (VS) 来克服超快成像中的视野 (FOV) 限制.
- 目前的VS放置策略使用确定性分布,导致图像分辨率和对比度之间的权衡.
研究的目的:
- 在分离波成像 (DWI) 中优化虚拟源 (VS) 对凸数组的空间分布.
- 提高图像质量指标,包括分辨率和对比率.
- 调查与减少传输事件的性能权衡.
主要方法:
- 开发了一种多目标遗传算法,以优化VS空间分布.
- 整合了复合面罩权重策略,以提高光束连贯性和减少工件.
- 在模拟和实验中使用点传播函数 (PSF) 度量 (FWHM,PSL) 和图像质量度量 (CR,SNR) 进行性能评估.
主要成果:
- 优化的VS分布实现了在半最大时全宽度 (FWHM) 降低高达50%.
- 与确定性方法相比,在对比率 (CR) 中表现出高达60%的改进.
- 即使在减少传输事件数量的情况下,也保持了性能增长.
结论:
- 拟议的多目标遗传算法有效地优化了VS配置,以提高DWI性能.
- 这种方法在凸数组的决定性VS分布方法上提供了显著的进步.
- 该方法为在超快超声波中平衡图像质量和传输效率提供了一个框架.
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