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Aneurysm management involves either conservative medical therapy or surgical intervention, depending on the size and symptoms of the aneurysm. Conservative management is generally reserved for smaller, asymptomatic aneurysms, while larger or symptomatic aneurysms often necessitate surgical repair.Conservative Medical TherapyFor small, asymptomatic aneurysms, particularly abdominal aortic aneurysms (AAA) less than 5.5 centimeters in diameter, conservative medical therapy is recommended. This...

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自主监督的光流量校正网络用于基于扩散方程的光声断层扫描.

Zhaoyong Liang1,2,3, Zongxin Mo1,2,3, Shuangyang Zhang1,2,3

  • 1School of Biomedical Engineering, Southern Medical University, 1023 Shatai Rd., Baiyun District, Guangzhou, Guangdong 510515, China.

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概括

本研究介绍了SQPA-Net,这是一种自主监督的深度学习方法,用于定量光声断层扫描 (QPAT),它可以在没有地面真相数据的情况下纠正光流动. 这种新的方法提高了准确性,并大大减少了生物组织成像的处理时间.

关键词:
吸收系数估计估计照明流动性校正光的流动性校正定量光声学断层扫描 (QPAT) 是一种量化光声学断层扫描.自主监督学习学习

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科学领域:

  • 生物医学成像技术 生物医学成像技术
  • 光学成像技术的成像
  • 摄影声学 摄影声学

背景情况:

  • 定量光声学断层扫描 (QPAT) 对于可视化组织特性至关重要.
  • 深度学习 (DL) 方法显示了QPAT的潜力,但需要广泛的基础真相数据进行培训.
  • 估计光流量分布对于准确的QPAT至关重要.

研究的目的:

  • 开发一种自我监督的深度学习方法,用于QPAT中的光流率校正.
  • 为了实现准确的QPAT,而不需要地面真相数据.
  • 为了提高QPAT成像的效率和准确性.

主要方法:

  • 为QPAT提出了一个自我监督的深度学习网络 (SQPA-Net).
  • 基于扩散方程的光流率估计集成到网络的损失函数中.
  • 仅使用原始的光声学 (PA) 图像训练网络.

主要成果:

  • 在QPAT中,SQPA-Net有效地纠正光流量分布.
  • 与传统的代方法和当前基于DL的方法相比,该方法显示出更高的性能.
  • 实现了显著减少图像处理时间.

结论:

  • 在QPAT中,SQPA-Net提供了一种有效和高效的解决方案,用于QPAT中的光流率校正.
  • 自主监督的方法克服了要求地面真相数据的局限性.
  • 这种方法推进了DL在定量光声成像中的应用.