Mireles Miguel, Xu Edward, Ragunathan Rahul, Fang Qianqian
Department of Bioengineering, Northeastern University, Boston 02115, USA.
Biomed Opt Express. 2024 Aug 8;15(9):5128-5142. doi: 10.1364/BOE.529195. eCollection 2024 Sep 1.
The low spatial resolution of diffuse optical tomography (DOT) has motivated the development of high-density DOT systems utilizing spatially-encoded illumination and detection strategies. Data compression methods, through the application of Fourier or Hadamard patterns, have been commonly explored for both illumination and detection but were largely limited to pre-determined patterns regardless of imaging targets. Here, we show that target-optimized detection patterns can yield significantly improved DOT reconstructions in both and experimental tests. Applying reciprocity, we can further iteratively optimize both illumination and detection patterns and show that these simultaneously optimized source/detection patterns outperform predetermined patterns in simulation settings. In addition, we show media-adaptive measurement data compression methods enable wide-field DOT systems to recover highly complex inclusions inside optically-thick media with reduced background artifacts. Furthermore, using truncated optimized patterns shows an improvement of 2-4× in increased speed of data acquisition and reconstruction without significantly losing image quality. The proposed method can be readily extended for additional data dimensions such as spectrum and time.
扩散光学层析成像（DOT）的低空间分辨率推动了利用空间编码照明和检测策略的高密度DOT系统的发展。通过应用傅里叶或哈达玛模式的数据压缩方法，已被广泛用于照明和检测，但无论成像目标如何，都很大程度上局限于预定模式。在这里，我们表明，目标优化的检测模式在模拟和实验测试中都能显著改善DOT重建。应用互易性，我们可以进一步迭代优化照明和检测模式，并表明这些同时优化的源/检测模式在模拟设置中优于预定模式。此外，我们表明介质自适应测量数据压缩方法使宽场DOT系统能够在光学厚介质中恢复高度复杂的内含物，同时减少背景伪影。此外，使用截断的优化模式显示，在不显著损失图像质量的情况下，数据采集和重建速度提高了2至4倍。所提出的方法可以很容易地扩展到其他数据维度，如光谱和时间。
