1. Articles from Zhiyu Huang

    1-8 of 8
    1. Weakly Supervised Deep Learning-Based Optical Coherence Tomography Angiography

      Weakly Supervised Deep Learning-Based Optical Coherence Tomography Angiography

      Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Deep learning networks have been widely applied in the field of OCTA reconstruction, benefiting from its powerful mapping capability among images. However, these existing deep learning-based methods depend on high-quality labels, which are hard to acquire considering imaging hardware limitations and practical data acquisition conditions. In this article, we proposed an unprecedented weakly supervised deep learning-based pipeline for OCTA reconstruction task, in the absence of high-quality training labels. The proposed pipeline was investigated on an in vivo animal dataset and a human eye dataset by a cross-validation ...

      Read Full Article
    2. Weakly Supervised Deep Learning Based Optical Coherence Tomography Angiography

      Weakly Supervised Deep Learning Based Optical Coherence Tomography Angiography

      Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Deep learning networks have been widely applied in the field of OCTA reconstruction, benefiting from its powerful mapping capability among images. However, these existing deep learning-based methods depend on high-quality labels, which are hard to acquire considering imaging hardware limitations and practical data acquisition conditions. In this paper, we proposed an unprecedented weakly supervised deep learning-based pipeline for OCTA reconstruction task, in the absence of high-quality training labels. The proposed pipeline was investigated on an in vivo animal dataset and a human eye dataset by a cross-validation ...

      Read Full Article
    3. N2NSR‐OCT: Simultaneous denoising and super‐resolution in optical coherence tomography images using semi‐supervised deep learning

      N2NSR‐OCT: Simultaneous denoising and super‐resolution in optical coherence tomography images using semi‐supervised deep learning

      Optical coherence tomography (OCT) imaging shows a significant potential in clinical routines due to its noninvasive property. However, the quality of OCT images is generally limited by inherent speckle noise of OCT imaging and low sampling rate. To obtain high signal‐to‐noise ratio (SNR) and high‐resolution (HR) OCT images within a short scanning time, we presented a learning‐based method to recover high‐quality OCT images from noisy and low‐resolution OCT images. We proposed a semi‐supervised learning approach named N2NSR‐OCT, to generate denoised and super‐resolved OCT images simultaneously using up‐ and down‐sampling networks ...

      Read Full Article
    4. Retinal choroidal vessel imaging based on multi-wavelength fundus imaging with the guidance of optical coherence tomography

      Retinal choroidal vessel imaging based on multi-wavelength fundus imaging with the guidance of optical coherence tomography

      A multispectral fundus camera (MSFC), as a novel noninvasive technology, uses an extensive range of monochromatic light sources that enable the view of different sectional planes of the retinal and choroidal structures. However, MSFC imaging involves complex processes affected by various factors, and the recognized theory based on light absorption above the choroid is not sufficient. In an attempt to supplement the relevant explanations, in this study, we used optical coherence tomography (OCT), a three-dimensional tomography modality, to analyze MSFC results at the retina and choroid. The swept-source OCT system at 1060 nm wavelength with a 200 kHz A-scan rate ...

      Read Full Article
    5. Resolution-matched reflection mode photoacoustic microscopy and optical coherence tomography dual modality system

      Resolution-matched reflection mode photoacoustic microscopy and optical coherence tomography dual modality system

      Photoacoustic microscopy (PAM) and optical coherence tomography (OCT) are sensitive to optical absorption and scattering characteristics, respectively. As such, the integration of these two modalities in order to combine important complementary information has garnered much attention. Due to the relatively low axial resolution of PAM, PAM and OCT dual modality systems generally have a large resolution gap, especially for reflection mode systems. In this study, based on a wide-band transparent pure-optical ultrasonic detector, we developed a dual modality system (PAM-OCT system) in which PAM has a similar spatial resolution (i.e. several micrometers in both the lateral and axial directions ...

      Read Full Article
    6. Comparative study of deep learning models for optical coherence tomography angiography

      Comparative study of deep learning models for optical coherence tomography angiography

      Optical coherence tomography angiography (OCTA) is a promising imaging modality for microvasculature studies. Meanwhile, deep learning has achieved rapid development in image-to-image translation tasks. Some studies have proposed applying deep learning models to OCTA reconstruction and have obtained preliminary results. However, current studies are mostly limited to a few specific deep neural networks. In this paper, we conducted a comparative study to investigate OCTA reconstruction using deep learning models. Four representative network architectures including single-path models, U-shaped models, generative adversarial network (GAN)-based models and multi-path models were investigated on a dataset of OCTA images acquired from rat brains. Three ...

      Read Full Article
    7. Noise reduction in optical coherence tomography images using a deep neural network with perceptually-sensitive loss function

      Noise reduction in optical coherence tomography images using a deep neural network with perceptually-sensitive loss function

      Optical coherence tomography (OCT) is susceptible to the coherent noise, which is the speckle noise that deteriorates contrast and the detail structural information of OCT images, thus imposing significant limitations on the diagnostic capability of OCT. In this paper, we propose a novel OCT image denoising method by using an end-to-end deep learning network with a perceptually-sensitive loss function. The method has been validated on OCT images acquired from healthy volunteers’ eyes. The label images for training and evaluating OCT denoising deep learning models are images generated by averaging 50 frames of respective registered B-scans acquired from a region with ...

      Read Full Article
    8. Adaptive classifier allows enhanced flow contrast in OCT angiography using a histogram-based motion threshold and 3D Hessian analysis-based shape filtering

      Adaptive classifier allows enhanced flow contrast in OCT angiography using a histogram-based motion threshold and 3D Hessian analysis-based shape filtering

      In this Letter, we propose an adaptive digital classifier for flow contrast enhancement in optical coherence tomography angiography (OCTA). To solve the depth dependence in the initial motion-based classification, a depth-adaptive motion threshold was determined by performing a histogram analysis of an en-face image at each depth and identifying the static and dynamic voxel populations through fitting. In the follow-up shape-based classification, to adapt to the deformed vessel shapes in OCTA, a modified vesselness function along with an anisotropic Gaussian probe kernel was defined, and then a three-dimensional (3D) Hessian analysis-based shape filtering was utilized for effectively removing the residual ...

      Read Full Article
    1-8 of 8
  1. Categories

    1. Applications:

      Art, Cardiology, Dentistry, Dermatology, Developmental Biology, Gastroenterology, Gynecology, Microscopy, NDE/NDT, Neurology, Oncology, Ophthalmology, Other Non-Medical, Otolaryngology, Pulmonology, Urology
    2. Business News:

      Acquisition, Clinical Trials, Funding, Other Business News, Partnership, Patents
    3. Technology:

      Broadband Sources, Probes, Tunable Sources
    4. Miscellaneous:

      Jobs & Studentships, Student Theses, Textbooks
  2. Topics in the News

    1. (7 articles) Peking University
    2. (5 articles) Qiushi Ren
    3. (4 articles) University of Erlangen
    4. (3 articles) Gangjun Liu
    5. (1 articles) Zhejiang University
    6. (1 articles) Chuanqing Zhou
    7. (1 articles) Peng Li
  3. Popular Articles

  4. Picture Gallery

    Adaptive classifier allows enhanced flow contrast in OCT angiography using a histogram-based motion threshold and 3D Hessian analysis-based shape filtering Noise reduction in optical coherence tomography images using a deep neural network with perceptually-sensitive loss function Comparative study of deep learning models for optical coherence tomography angiography Resolution-matched reflection mode photoacoustic microscopy and optical coherence tomography dual modality system Retinal choroidal vessel imaging based on multi-wavelength fundus imaging with the guidance of optical coherence tomography N2NSR‐OCT: Simultaneous denoising and super‐resolution in optical coherence tomography images using semi‐supervised deep learning Weakly Supervised Deep Learning Based Optical Coherence Tomography Angiography Weakly Supervised Deep Learning-Based Optical Coherence Tomography Angiography Customized Slab-Segmentation Method for Projection-Artifact Elimination in Best Vitelliform Macular Dystrophy: A Swept-Source Optical Coherence Tomography Angiography Study Corneal Epithelial Thickness Profile in Healthy Portuguese Children by High-Definition Optical Coherence Tomography Prediction model for best focus, power, and spherical aberration of the cornea: Raytracing on a large dataset of OCT data Classification of pachychoroid on optical coherence tomography using deep learning