Titlebook: Retinal Optical Coherence Tomography Image Analysis; Xinjian Chen,Fei Shi,Haoyu Chen Book 2019 Science Press and Springer Nature Singapore

入伍儀式

Clinical Applications of Retinal Optical Coherence Tomography,. This chapter introduces anatomy of the eye and the retina, describes various types of eye diseases that can be visualized with OCT imaging, and therefore presents the must-know background knowledge for readers interested in retinal OCT image analysis.

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Speckle Noise Reduction and Enhancement for OCT Images,uction, which is helpful for more sophisticated processes like segmentation. Three OCT despeckling and enhancement methods are presented in this chapter, which are based on statistical modeling, data adaptive and non data adaptive transform based models, respectively.

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Reconstruction of Retinal OCT Images with Sparse Representation,rden for storage and transmission. To alleviate these problems, this chapter introduces several sparse representation based reconstruction methods for denoising, interpolation and compression, which enhance the quality of the OCT images and efficiently manage such large of amounts of data.

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整體

Segmentation of Optic Disc and Cup-to-Disc Ratio Quantification Based on OCT Scans, chapter, an automated algorithm is presented for optic disc segmentation in 3-D spectral domain optical coherence tomography, based on which the cup-to-disc ratio an important indicator of early glaucoma can be calculated.

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Choroidal OCT Analytics,s associated with various diseases. In this chapter, methodologies are presented for automatic quantification of choroidal measurements such as thickness, volume and stromal-luminal ratio, which are indicators crucial in disease diagnosis and treatment response monitoring.

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Book 2019d state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging..

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