Image Reconstruction in Functional Optical Neuroimaging The modelling and separation of the scalp blood flow: A research proposal

Optical imaging is an emerging modality to image biological tissue non-invasively. Its use for brain imaging function is known as functional Near Infrared Spectroscopy (fNIRS). Its use as a functional neuroimaging modality demands attending numerous factors many which are still being investigated. One of these factors is the image reconstruction, particularly critical for brain understanding. The main problem to investigate in this research is the inherent inverse problem of the optical neuroimage reconstruction in which several sources of noise exist aggravating the ill-posed nature of the problem. Popular methods address this problem with strong assumptions leading to a reconstruction departing from reality. In order to alleviate this situation, this research, aims to develop a reconstruction based on a precise model of the forward problem, the quantification of the noise due to the blood irrigation in the scalp as one of the leading artefacts affecting reconstruction and the use of this information as an a priori knowledge in order to improve reconstruction. The main scientific contributions will be; the better understanding of the image formation process in the optical neuroimage domain, the more accurate forward model developed, the quantification of noise from scalp irrigation and the solution to the inverse problem informed with the a priory knowledge. Preliminary results shows that reconstruction is more viable when the source of noise is avoided.