1. Articles from Ping Li

    1-3 of 3
    1. Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

      Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning

      The choroid layer is a vascular layer in human retina and its main function is to provide oxygen and support to the retina. Various studies have shown that the thickness of the choroid layer is correlated with the diagnosis of several ophthalmic diseases. For example, diabetic macular edema (DME) is a leading cause of vision loss in patients with diabetes. Despite contemporary advances, automatic segmentation of the choroid layer remains a challenging task due to low contrast, inhomogeneous intensity, inconsistent texture and ambiguous boundaries between the choroid and sclera in Optical Coherence Tomography (OCT) images. The majority of currently implemented ...

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    2. Automatic Subretinal Fluid Segmentation of Retinal SD-OCT Images With Neurosensory Retinal Detachment Guided by Enface Fundus Imaging

      Automatic Subretinal Fluid Segmentation of Retinal SD-OCT Images With Neurosensory Retinal Detachment Guided by Enface Fundus Imaging

      Objective: Accurate segmentation of neurosensory retinal detachment (NRD) associated subretinal fluid in spectral domain optical coherence tomography (SD-OCT) is vital for the assessment of central serous chorioretinopathy (CSC). A novel two-stage segmentation algorithm was proposed, guided by Enface fundus imaging. Methods: In the first stage, Enface fundus image was segmented using thickness map prior to detecting the fluid-associated abnormalities with diffuse boundaries. In the second stage, the locations of the abnormalities were used to restrict the spatial extent of the fluid region, and a fuzzy level set method with a spatial smoothness constraint was applied to subretinal fluid segmentation in ...

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    3. Phase registration based on matching of phase distribution characteristics and its application in FDOCT

      Phase registration based on matching of phase distribution characteristics and its application in FDOCT

      Phase fluctuations in a two-transverse-dimensional scanning Fourier domain optical coherence tomography (FDOCT) seriously affect in vivo phase related applications. The phase difference between two A-scans sampled at the same scanning position or adjacent scanning position is acquired by matching of the phase distribution characteristics on the surface of two A-scans. Finger and palm scanning experiments are performed and defocused images of finger and palm are recovered based on Fresnel scalar diffraction algorithm by using phase compensated OCT complex signals. To further prove the performance of the proposed method, human eye scanning experiments are also performed and blood flow images of ...

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    1-3 of 3
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    1. (1 articles) Sungkyunkwan University
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    Phase registration based on matching of phase distribution characteristics and its application in FDOCT Automatic Subretinal Fluid Segmentation of Retinal SD-OCT Images With Neurosensory Retinal Detachment Guided by Enface Fundus Imaging Automatic Choroid Layer Segmentation from Optical Coherence Tomography Images Using Deep Learning High space-bandwidth in quantitative phase imaging using partially spatially coherent optical coherence microscopy and deep neural network Optical coherence tomography assessment of macrophages accumulation in non-ST-segment elevation acute coronary syndromes Early disability in ambulatory patients with multiple sclerosis: optical coherence tomography versus visual evoked potentials, a comparative study Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes Atlas of Optical Coherence Tomography for Glaucoma (Textbook) In-vivo analysis of iron-gold composite nanoparticles as potential exogenous contrast agents for Magnetomotive Optical Coherence Tomography (MMOCT) Automatic Classification of Volumetric Optical Coherence Tomography Images via Recurrent Neural Network Noise-Powered Disentangled Representation for Unsupervised Speckle Reduction of Optical Coherence Tomography Images Circadian variations in pathogenesis of ST-segment elevation myocardial infarction: an optical coherence tomography study