Seeing Beneath the Skin with Computational Photography

FROM X-RAYS TO magnetic resonance imaging (MRI), methods for scanning the body have transformed how we understand and care for our health. These non-invasive techniques allow clinicians to observe and diagnose conditions while minimizing risks to the patient from invasive medical procedures. Recently, methods using red-green-blue (RGB) and nearinfrared (NIR) cameras, other photosensors, such as more specialized and sophisticated tomography,(6,8,40) and radio waves and Wi-Fi signals have enabled a range of new non-invasive and non-contact health monitoring techniques.(1,8,12,21,22,26,28,32,33,40) Human tissue interaction with visible and infra-red light is predominantly through scattering. There are two immediate consequences to this light scattering by tissue. Firstly, since the scattering is predominantly forward-scattering, photons can still illuminate deep into human tissue providing the potential to use light to image beneath the skin. Secondly, diffuse scattering, by definition diffuses the spatial coherence and localization in light patterns, making conventional imaging challenging. But the statistical and structural regularity present even in diffuse scattering provides us with the potential that computational demultiplexing algorithms along with imaging systems can provide sufficient spatial resolution in deep tissue imaging to be clinically useful.