Time-domain diffuse optical tomography with l_p sparsity regularization for thyroid cancer imaging

Diffuse optical tomography (DOT) images the distribution of the optical properties, such as the absorption and scattering coefficients, via the image reconstruction from the light intensities measured at the surface of the biological medium. The changes in the optical properties reflect the conditions of the tissues. Therefore, DOT image can provide the information which is not obtained from the other modalities and is useful for medical diagnoses. In this study, the application of the DOT to thyroid cancer diagnosis was investigated. The ultrasound technique is usually carried out for the thyroid cancer diagnosis. It is, however, difficult to distinguish follicular carcinoma from adenoma of thyroid. The optical properties may be helpful for the diagnosis. The image reconstruction algorithm employing the regularization minimizing l_p-norm (0 < p < 2) of the reconstructed image was developed. The image was reconstructed from the time-resolved measurement data. The numerical simulations of the image reconstruction were tried. The numerical simulation demonstrated that the developed algorithm was able to image the changes in the optical properties in the medium. Additionally, the image reconstruction of the numerical neck phantom was simulated. The thyroid cancer region was reconstructed successfully. It was demonstrated that the developed algorithm had the possibility to image thyroid cancer.