1. Articles from LIYANG FANG

    1-3 of 3
    1. Automatic Segmentation and Visualization of Choroid in OCT with Knowledge Infused Deep Learning

      Automatic Segmentation and Visualization of Choroid in OCT with Knowledge Infused Deep Learning

      The choroid provides oxygen and nourishment to the outer retina thus is related to the pathology of various ocular diseases. Optical coherence tomography (OCT) is advantageous in visualizing and quantifying the choroid in vivo, because it does not suffer from the information contamination of the outer retina in fundus photography and scanning laser ophthalmoscopy and the resolution deficiency in ocular ultrasound. We propose a biomarker infused global-to-local network, for the choroid segmentation. It leverages the thickness of the choroid layer, which is a primary biomarker in clinic, as a constraint to improve the segmentation accuracy. We also design a global-to-local ...

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    2. High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning

      High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning

      Reducing the bit-depth is an effective approach to lower the cost of optical coherence tomography (OCT) systems and increase the transmission efficiency in data acquisition and telemedicine. However, a low bit-depth will lead to the degeneration of the detection sensitivity thus reduce the signal-to-noise ratio (SNR) of OCT images. In this paper, we propose to use deep learning for the reconstruction of the high SNR OCT images from the low bit-depth acquisition. Its feasibility was preliminarily evaluated by applying the proposed method to the quantized 3 ∼ 8-bit data from native 12-bit interference fringes. We employed a pixel-to-pixel generative adversarial network ...

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    3. Resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning

      Resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning

      Optical coherence tomography angiography (OCTA) requires high transverse sampling rates for visualizing retinal and choroidal capillaries, which impedes the popularization of the OCTA technique due to the high cost of speedy acquisition systems. On the other hand, current wide-field OCTA using low transverse sampling causes the underestimation of vascular biomarkers in quantitative analysis. In this paper, we propose to use deep learning to repair the resolution degeneration induced by the low transverse sampling. We conducted preliminary experiments on converting the centrally cropped 3 × 3 mm2 field of view (FOV) of the 8 × 8 mm2 foveal OCTA images (a sampling rate ...

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    1-3 of 3
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    1. (1 articles) Sun Yat-Sen University
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    Resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning Automatic Segmentation and Visualization of Choroid in OCT with Knowledge Infused Deep Learning Optical coherence tomography angiography (OCTA) findings in Serpiginous Choroiditis Changes in retinal layer thickness with maturation in the dog: an in vivo spectral domain - optical coherence tomography imaging study Optical coherence tomography angiography analysis of fabry disease An unsupervised hierarchical approach for automatic intra‐retinal cyst segmentation in spectral‐domain optical coherence tomography images Towards quantitative assessment of burn based on photoacoustic and optical coherence tomography Cellular Scale Imaging of Transparent Retinal Structures and Processes Using Adaptive Optics Optical Coherence Tomography Optical Coherence Tomography Imaging in Acute Myocardial Infarction: Calcified Nodule as a Culprit Lesion Study of low-peak-power highly coherent broadband supercontinuum generation through a dispersion-engineered Si-rich silicon nitride waveguide Invasive Coronary Artery Imaging Using Optical Coherence Tomography: A Cost-effectiveness and Implementation Process Analysis (Thesis)