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对于NIR-II光分子断层扫描的深度系统先前基于图形卷积网络
Beilei Wang1, Shuangchen Li1, Heng Zhang1
1School of Information Sciences and Technology, Northwest University, Xi'an, 710127, People's Republic of China; The Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, People's Republic of China.
Computer methods and programs in biomedicine
|July 20, 2025
概括
本研究介绍了用于光分子断层扫描 (FMT) 的深度系统先前基于图形卷积网络 (DSPGN). DSPGN在第二近红外窗 (NIR-II) 成像中提高了瘤位置精度和形状恢复.
科学领域:
- 生物医学成像技术 生物医学成像技术
- 医学物理 医学物理
- 计算成像技术的成像
背景情况:
- 光分子断层扫描 (FMT) 对早期瘤检测非常有价值.
- 在FMT中严重的光子散射导致错误的反向问题,阻碍了准确性和形态重建.
- 目前的FMT方法很难满足精确瘤成像的实际要求.
研究的目的:
- 提高FMT的效率和准确性.
- 为了提高FMT重建的形态性能.
- 为了解决由光子散射引起的FMT的不良位置性质.
主要方法:
- 使用第二次近红外 (NIR-II) 光成像来减少组织散射.
- 开发了一个深度系统基于前置图形卷积网络 (DSPGN) 的FMT.
- 将系统空间前置和图形结构纳入重建过程中.
主要成果:
- 与现有方法相比,DSPGN在定位准确性方面表现优越.
- 拟议的方法显著提高了FMT的形状恢复能力.
- 数字模拟和体内实验都验证了DSPGN的有效性.
结论:
- DSPGN有效地恢复光源的位置和形态.
- 该方法显示了在NIR-II成像中推进FMT应用的潜力.
- DSPGN为克服FMT固有的挑战提供了一个有希望的解决方案.
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