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光-NeRF:光神经辐射场用于超声计算机断层成像中的强大的声速成像

Shilong Cui, Qing Wu, Yiming Huang

IEEE transactions on ultrasonics, ferroelectrics, and frequency control

|March 26, 2025

概括

曲射线神经辐射场 (BentRay-NeRF) 改善了用于乳腺癌检测的超声波计算机断层扫描. 这种新方法提高了声音图像重建的速度,提供比传统技术更稳定,更高质量的结果.

科学领域:

医疗成像医学成像
计算物理计算物理
人工智能的人工智能

背景情况:

超声波计算机断层扫描 (USCT) 使用声速 (SOS) 来检测乳腺癌,因为恶性组织表现出更高的SOS.
曲射线追踪USCT对于大规模查具有计算效率,但面临着不良条件的SOS图像重建和测量错误的挑战.

研究的目的:

为了解决SOS图像重建在曲射线追踪USCT的不良性质.
通过隐式神经表示来引入一种用于稳定和高质量的SOS图像重建的新方法.

主要方法:

开发了曲射线神经辐射场 (BentRay-NeRF) 方法,使用具有哈希编码的多层感知子来建模缓慢地图.
利用隐式神经表示 (INR) 来规范反向问题,为传统规范化术语提供了替代方案.
将BentRay-NeRF与SOS图像重建的高斯-牛顿等经典方法进行比较.

主要成果:

在SOS图像重建中,BentRay-NeRF有效地减轻了条件不良的问题.
该方法证明了稳定和高质量的重建,优于经典方法.
实验显示,图像质量和对测量误差和不同采集设置的稳定性得到了改善.

结论:

隐式神经表示,特别是BentRay-NeRF,为USCT中的SOS图像重建提供了显著的进步.
这种方法提高了使用USCT检测乳腺癌的可靠性和准确性.
"BentRay-NeRF"为克服传统重建技术的局限性提供了一个有希望的解决方案.

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