Multiscale joint segmentation method for retinal optical coherence tomography images using a bidirectional wave algorithm and improved graph theory.

Morphology and functional metrics of retinal layers are important biomarkers for many human ophthalmic diseases. Automatic and accurate segmentation of retinal layers is crucial for disease diagnosis and research. To improve the performance of retinal layer segmentation, a multiscale joint segmentation framework for retinal optical coherence tomography (OCT) images based on bidirectional wave algorithm and improved graph theory is proposed. In this framework, the bidirectional wave algorithm was used to segment edge information in multiscale images, and the improved graph theory was used to modify edge information globally, to realize automatic and accurate segmentation of eight retinal layer boundaries. This framework was tested on two public datasets and two OCT imaging systems. The test results show that, compared with other state-of-the-art methods, this framework does not need data pre-training and parameter pre-adjustment on different datasets, and can achieve sub-pixel retinal layer segmentation on a low-configuration computer.

Fast OCT image enhancement method based on the sigmoid-energy conservation equation.

Optical coherence tomography (OCT) is an important medical diagnosis technology, but OCT images are inevitably interfered by speckle noise and other factors, which greatly reduce the quality of the OCT image. In order to improve the quality of the OCT image quickly, a fast OCT image enhancement method is proposed based on the fusion equation. The proposed method consists of three parts: edge detection, noise suppression, and image fusion. In this paper, the improved wave algorithm is used to detect the image edge and its fine features, and the averaging uncorrelated images method is used to suppress speckle noise and improve image contrast. In order to sharpen image edges while suppressing the speckle noise, a sigmoid-energy conservation equation (SE equation) is designed to fuse the edge detection image and the noise suppression image. The proposed method was tested on two publicly available datasets. Results show that the proposed method can effectively improve image contrast and sharpen image edges while suppressing the speckle noise. Compared with other state-of-the-art methods, the proposed method has better image enhancement effect and speed. Under the same or better enhancement effect, the processing speed of the proposed method is 2 ∼ 34 times faster than other methods.

Application of optical coherence tomography in clinical diagnosis.

BACKGROUND: Optical coherence tomography (OCT) is a non-invasive diagnosing tool used in clinics. Due to its high resolution (<10um), it is appropriate for the early detection of tiny infections. It has been widely used in diagnosis and treatment of diseases, evaluation of therapeutic efficacy, and monitoring of various physiological and pathological processes. OBJECTIVE: To systemically review literature to summarize the clinic application of OCT in recent years. METHODS: For clinic applications that OCT has been applied, we selected studies that describe the most relevant works. The discussion included: 1) which tissue could be used in the OCT detection, 2) which character of different tissue could be used as diagnosing criteria, 3) which diseases and pathological process have been diagnosed or monitored using OCT imaging, and 4) the recent development of clinic OCT diagnosing. RESULTS: The literature showed that the OCT had been listed as a routine test choice for ophthalmic diseases, while the first commercial product for cardiovascular OCT detection had gotten clearance. Meanwhile, as the development of commercial benchtop OCT equipment and tiny fiber probe, the commercial application of OCT in dermatology, dentistry, gastroenterology and urology also had great potential in the near future. CONCLUSIONS: The analysis and discussions showed that OCT, as an optical diagnosing method, has been used successfully in many clinical fields, and has the potential to be a standard inspection method in several clinic fields, such as dermatology, dentistry and cardiovascular.

Design of optical system for binocular fundus camera.

A non-mydriasis optical system for binocular fundus camera has been designed in this paper. It can capture two images of the same fundus retinal region from different angles at the same time, and can be used to achieve three-dimensional reconstruction of fundus. It is composed of imaging system and illumination system. In imaging system, Gullstrand Le Grand eye model is used to simulate normal human eye, and Schematic eye model is used to test the influence of ametropia in human eye on imaging quality. Annular aperture and black dot board are added into illumination system, so that the illumination system can eliminate stray light produced by corneal-reflected light and omentoscopic lens. Simulation results show that MTF of each visual field at the cut-off frequency of 90lp/mm is greater than 0.2, system distortion value is -2.7%, field curvature is less than 0.1 mm, radius of Airy disc is 3.25um. This system has a strong ability of chromatic aberration correction and focusing, and can image clearly for human fundus in which the range of diopters is from -10 D to +6 D(1 D = 1 m-1).