Abstract
Diffuse optical tomography (DOT) is an advanced imaging method used to visualize the internal state of biological tissues as 3D images. However, current continuous-wave DOT requires high-density probe arrays for measurement (less than 15-mm interval) to gather enough information for 3D image reconstruction, which makes the experiment time-consuming. In this paper, we propose a novel DOT measurement system using multi-directional light sources and multi-directional photodetectors instead of high-density probe arrays. We evaluated this system's multi-directional DOT through computer simulation and a phantom experiment. From the results, we achieved DOT with less than 5-mm localization error up to a 15-mm depth with low-density probe arrays (30-mm interval), indicating that the multi-directional measurement approach allows DOT without requiring high-density measurement.
Highlights
Diffuse optical imaging is a method used to visualize the internal state of biological tissues using near-infrared (NIR) light
NIR light is more transmissive than surrounding bands in biological tissues and can be used to measure the oxygenation level of hemoglobin when applied with spectroscopic techniques (NIRS)
We proposed and developed a novel multi-directional optical measurement system for diffuse optical tomography
Summary
Diffuse optical imaging is a method used to visualize the internal state of biological tissues using near-infrared (NIR) light. Compared to large-scale imaging modalities such as X-ray computed tomography or magnetic resonance imaging (MRI), diffuse optical imaging has such advantages as the safety of NIR light, produced with a portable device at low cost, and few physical restrictions in measurement. These merits permit anyone, including babies, elderly people, and patients with an implanted electronic device, to be measured in a natural environment. For three-dimensional imaging, it is necessary to obtain sufficiently richer measurement information to reconstruct internal tissues, and the development of a sophisticated image reconstruction algorithm is required
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