Study On Key Problems Of Fourier Transform Spectrum Detection Device In Optical Coherence Tomography

Spectral Domain Optical Coherence Tomography (SDOCT) is a kind of high resolution tomographic imaging technology. SDOCT can detect the spectral interference information created by the backscatter light from the biological tissue and the light form the reference mirror to rebuild two-dimensional optical tomography images of biological tissue. The key to make SDOCT system practical is the problem of detecting the interference spectral information. This paper will study several key problems of the MEMS based micro Fourier Spectral detection device of the Optical Coherence Tomography.The paper first describes the background of the SDOCT and spectrometer, then introduced the basic classification of spectrometer, the MEMS technology and the current research at home and abroad. Then analyzes the basic principle of FTS, describes the data sampling system, laser calibration algorithms and the spectrometer index calculation method, etc. Then analyze the movement characteristics of MEMS mirror, focusing on the several situations’effect on the spectral stability, like the change of total travel distance, speed, perpendicularity and initial position of the mirror. To solve the problems above, then innovatively propose dual-optical real-time calibration design to solve the horizontal drift of spectrum. Propose equal periodic interception algorithm to increase the instrument’s repeatability index by about 3 times. Propose a new equal interpolation of displacement algorithm by using the Hilbert transform to get the instantaneous phase information of laser, this algorithm can make full use of the raw data, increase the usage of laser signal data about 40 times, and decrease the wavelength accuracy from the difference of 3 nm to 1 nm. Finally carry out Design of Experiment (DOE) for the key algorithms and factors which can affect the instrument’s stability, get the most significant factor affecting instrument performance is the temperature factor and give the optimal combination of main parameters in the spectrum recovery algorithms.