Study On Signal And Image Processing Methods In Optical Coherence Tomography

Optical coherence tomography (OCT) is a novel medical diagnosis technique based on the coherence of wide band source to obtain images of microstructure of biological tissues. It has a great number of advantages including high spatial resolution, in vivo and real-time operation, and non-contact, and non-invasive properties, which makes it be applied to wide biological and medical fields. Owing to the inherent nature of the imaging system and the detection method, OCT system suffers from different noises which degrade the quality of the images. Also, the multiple scattering in these high scattered biological tissues make it hard to distinguish the internal details of specimen in unprocessed OCT image due to a relatively low contrast.Based on the OCT system in our laboratory, image processing techniques will be discussed to optimize the OCT image in the paper. With the discussion of the available image processing techniques and theories, algorithms for sidelobe suppression, noise reduction and contrast enhancement have been proposed, and experiments demonstrated the effective of the algorithms. The main achievements and the innovative ideas of our research are outlined in the following:1. A gradual iterative signal subtraction method based on the study of a point signal influenced by other points with different distances through the PSF is proposed to suppress the sidelobes in the OCT images.2. A method of image improvement based on the contrast measure in wavelet domain is presented to enhance the contrast of the OCT images.3. An adaptive wavelet denoising method which is on the basis of context modeling is applied before the image enhancement algorithm to reduce the effects of the noise when amplifying the signal...