Research On The Image Processing And Software Development Of Optical Coherence Tomography System

The optical coherence tomography(OCT)is one of the novel tomography imaging technique to get the microstructure image of biological tissue. It has many advantages, such as high resolution, non-invasion and non-contact detection. Therefore, it has been possessed of great development potential application in clinical medicine.In order to make OCT become a kind of practical medical diagnosis system, it is important to work on the data mining and processing of OCT image. The study on the OCT software system development in image acquisition and image processing modules are discussed. We hereby developed the operation system in our Fourier Domain Optical Coherence Tomography (FD-OCT)system and image segmentation algorithm.The control software includes the image acquisition, picture browsing, measurement and analysis, database management modules. It possesses the functions of patient information management, retinal image real-time collection, capturing of interferometer signals and data reconstructing,real-time fundus image, automatic segmentation of retinal layers, quantitative measurement of the retinal thickness, and displaying of the OCT images reconstructed in pseudo color and printing of the test report.To automatically extract the contour of the retinal sub-layers through image segmentation is not only a basic issue to the application of OCT in retinal diseases diagnosis, but also an important technology to the localization of OCT system. A multi-step approach which includes the filtering; peak detection; Snake model; greedy algorithm and spline interpolation was devised. Therefore, we realized automatic segmentation of retinal layers and quantitative measurement of the retinal thickness. The method has been successfully applied on a database of images of normal people's eyes. The automated thickness measurements derived by this algorithm is compared with thickness measurements from manually marked boundaries. A good agreement was obtained. In conclusion, the proposed approach is promising for investigating for retinal variability studies.