Maity Akash Kumar, Sharma Manoj Kumar, Veeraraghavan Ashok, Sabharwal Ashutosh
Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
Biomed Opt Express. 2023 Sep 20;14(10):5316-5337. doi: 10.1364/BOE.498900. eCollection 2023 Oct 1.
Laser speckle contrast imaging is widely used in clinical studies to monitor blood flow distribution. Speckle contrast tomography, similar to diffuse optical tomography, extends speckle contrast imaging to provide deep tissue blood flow information. However, the current speckle contrast tomography techniques suffer from poor spatial resolution and involve both computation and memory intensive reconstruction algorithms. In this work, we present SpeckleCam, a camera-based system to reconstruct high resolution 3D blood flow distribution deep inside the skin. Our approach replaces the traditional forward model using diffuse approximations with Monte-Carlo simulations-based convolutional forward model, which enables us to develop an improved deep tissue blood flow reconstruction algorithm. We show that our proposed approach can recover complex structures up to 6 mm deep inside a tissue-like scattering medium in the reflection geometry. We also conduct human experiments to demonstrate that our approach can detect reduced flow in major blood vessels during vascular occlusion.
激光散斑对比成像在临床研究中被广泛用于监测血流分布。散斑对比断层扫描类似于扩散光学断层扫描，它扩展了散斑对比成像以提供深部组织血流信息。然而，当前的散斑对比断层扫描技术存在空间分辨率差的问题，并且涉及计算量大和内存密集型的重建算法。在这项工作中，我们展示了SpeckleCam，这是一种基于相机的系统，用于重建皮肤内部深处的高分辨率三维血流分布。我们的方法用基于蒙特卡洛模拟的卷积正向模型取代了使用扩散近似的传统正向模型，这使我们能够开发一种改进的深部组织血流重建算法。我们表明，我们提出的方法能够在反射几何结构中恢复组织样散射介质内部达6毫米深处的复杂结构。我们还进行了人体实验，以证明我们的方法能够检测血管闭塞期间主要血管中血流的减少。
