Development of Signal Processing Algorithm for Optical Coherence Tomography

Optical Coherence Tomography (OCT) is a growing non-invasive imaging technology that is capable of generating high-resolution cross-sectional images and high processing speed. It is extensively used for the diagnosis of retinal diseases in ophthalmology, estimation of blood flow and in the field of oncology, cardiology, and dermatology as an imaging device. The spectral-domain OCT (SD-OCT) uses low coherence interferometry to get depth-resolved information of the sample with resolution in the micrometer range and imaging depth in the millimeter range. The complexity of the OCT algorithm demands high processing speed from the underlying platform. The aim is to develop the signal processing algorithm to achieve improved imaging depth. The methods such as background removal, re-sampling, FFT are used to get the desired depth profile of the sample. The response of the actual hardware model is predicted from the outputs. This depth profile gives the information of depth about the sample and the maximum depth depends on the number of pixel information obtained from the spectrometer.