Reconstruction algorithms for time-domain diffuse optical tomography imaging of small animals

这项提议是关于开发高效的计算机程序(所谓的算法)，以获得用于生物医学研究的小型实验室动物(小鼠)内部的3D图像。这里考虑的获取这些图像的技术是漫反射光学层析成像(DOT)，这是一种非侵入性的医学成像方式，使用来自激光的非电离光在动物皮肤的多个点上照明。从动物身上传播出来的光在皮肤上的几个位置再次被测量(检测)。算法的任务是从这样的表面测量数据中获得动物内部的3D图像。对于DOT来说，这是一个困难的数学问题，在现代台式计算机上，解决这个问题可能需要几个小时才能获得图像。此外，我们工作的一个特殊性是我们求助于一种检测技术，即所谓的时域光学测量，它提供了更丰富的信息数据。这有可能提高获得的图像的空间分辨率，使它们更定量，但由于必须用这种测量处理更多的数据，计算时间进一步增加。利用这样的数据促使高效的数值技术来减少我们的算法所需的计算能力。这项建议是关于这种技术的发展，这些技术应该会导致计算时间减少约10%到100%。这项研究很重要，因为小动物的3D临床前成像是生物医学研究的关键工具，可以研究疾病发展(癌症)和治疗(药物设计、治疗评估)所涉及的基本过程。这最终影响了可以提供给疾病患者的治疗质量，从而改善了他们的生活质量和预后。这里提出的研究计划将为DOT的最终用户提供关于他们的方案的更快的反馈，这在他们的日常工作中是重要的。值得注意的是，这里开发的光学成像允许研究无法用其他医学成像模式可视化的过程，从而补充这些其他模式。该提案将允许培养4名博士生，同时启动5名学士学位学生进行研究。

This proposal is about the development of efficient computer programs (so-called algorithms) to obtain images in 3D of the interior of small laboratory animals (mice) used in biomedical research. The technique considered here for obtaining these images is diffuse optical tomography (DOT), a non-invasive medical imaging modality whereby non-ionizing light from a laser is used to illuminate an animal at several points on its skin. The light exiting the animal after its propagation through its body is measured (detected) at several positions again on its skin. The task of algorithms is to obtain from such surface measurements data a 3D image of the interior of the animal. For DOT, this is a difficult mathematical problem whose solution may take up to several hours on modern desktop computers before an image is obtained. Furthermore, a particularity of our work is that we resort to a detection technique, so-called time-domain optical measurements, that provides for information richer data. This has the potential of improving the spatial resolution of the images obtained and making them more quantitative, but since more data must be handled with such measurements, the computing time is further increased. Exploiting such data prompts for efficient numerical techniques to reduce the computational power needed by our algorithms. This proposal is about the development of such techniques that should lead to a decrease in computing times by an estimated factor of 10 to 100. This research is important because 3D pre-clinical imaging of small animals is a key tool in biomedical research that allows studying fundamental processes involved in disease development (cancer) and treatment (drug design, therapy assessment). This ultimately has impacts on the quality of treatments that can be offered to diseased patients, thus improving their quality of life and prognostics. The research program proposed here will provide end-users of DOT with faster feedback on their protocols which is important in their daily duties. Notably, optical imaging as developed here, allows studying processes that cannot be visualized with other medical imaging modalities, thus complementing these other modalities. The proposal will allow training 4 doctoral degree students along with initiating 5 bachelor’s degree students to research.