1. Articles from robert t. chang

    1-12 of 12
    1. Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning

      Towards multi-center glaucoma OCT image screening with semi-supervised joint structure and function multi-task learning

      Glaucoma is the leading cause of irreversible blindness in the world. Structure and function assessments play an important role in diagnosing glaucoma. Nowadays, Optical Coherence Tomography (OCT) imaging gains increasing popularity in measuring the structural change of eyes. However, few automated methods have been developed based on OCT images to screen glaucoma. In this paper, we are the first to unify the structure analysis and function regression to distinguish glaucoma patients from normal controls effectively. Specifically, our method works in two steps: a semi-supervised learning strategy with smoothness assumption is first applied for the surrogate assignment of missing function regression ...

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    2. A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans

      A 3D Deep Learning System for Detecting Referable Glaucoma Using Full OCT Macular Cube Scans

      Purpose : The purpose of this study was to develop a 3D deep learning system from spectral domain optical coherence tomography (SD-OCT) macular cubes to differentiate between referable and nonreferable cases for glaucoma applied to real-world datasets to understand how this would affect the performance. Methods : There were 2805 Cirrus optical coherence tomography (OCT) macula volumes (Macula protocol 512 × 128) of 1095 eyes from 586 patients at a single site that were used to train a fully 3D convolutional neural network (CNN). Referable glaucoma included true glaucoma, pre-perimetric glaucoma, and high-risk suspects, based on qualitative fundus photographs, visual fields, OCT reports ...

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    3. Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis

      Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis

      Background Spectral-domain optical coherence tomography (SDOCT) can be used to detect glaucomatous optic neuropathy, but human expertise in interpretation of SDOCT is limited. We aimed to develop and validate a three-dimensional (3D) deep-learning system using SDOCT volumes to detect glaucomatous optic neuropathy. Methods We retrospectively collected a dataset including 4877 SDOCT volumes of optic disc cube for training (60%), testing (20%), and primary validation (20%) from electronic medical and research records at the Chinese University of Hong Kong Eye Centre (Hong Kong, China) and the Hong Kong Eye Hospital (Hong Kong, China). Residual network was used to build the 3D ...

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    4. Serial Spectral-Domain Optical Coherence Tomography Findings in Acute Retinal Pigment Epitheliitis and the Correlation to Visual Acuity

      Serial Spectral-Domain Optical Coherence Tomography Findings in Acute Retinal Pigment Epitheliitis and the Correlation to Visual Acuity

      Purpose To evaluate the features of acute retinal pigment epitheliitis (ARPE) at onset and in the course of recovery by serial spectral-domain optical coherence tomography (SD OCT) and the correlation to visual acuity (VA). Design Retrospective cohort study. Participants Consecutive patients with ARPE. Methods A review of medical records was performed. Main Outcome Measures Integrity of SD OCT retinal bands at onset and in the course of disease, time required to achieve each retinal band restoration, corresponding VA change, and final VA. Results Four patients were included. Initial SD OCT showed a dome-shaped hyper-reflective lesion at the photoreceptor outer segment ...

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    5. Diagnostic Performance of Optical Coherence Tomography Ganglion Cell–Inner Plexiform Layer Thickness Measurements in Early Glaucoma

      Diagnostic Performance of Optical Coherence Tomography Ganglion Cell–Inner Plexiform Layer Thickness Measurements in Early Glaucoma

      Purpose To evaluate the glaucoma diagnostic performance of ganglion cell inner–plexiform layer (GCIPL) parameters used individually and in combination with retinal nerve fiber layer (RNFL) or optic nerve head (ONH) parameters measured with Cirrus HD-OCT (Carl Zeiss Meditec, Inc, Dublin, CA). Design Prospective cross-sectional study. Participants Fifty patients with early perimetric glaucoma and 49 age-matched healthy subjects. Methods Three peripapillary RNFL and 3 macular GCIPL scans were obtained in 1 eye of each participant. A patient was considered glaucomatous if at least 2 of the 3 RNFL or GCIPL scans had the average or at least 1 sector measurement ...

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    6. Glaucoma Diagnostic Accuracy of Ganglion Cell–Inner Plexiform Layer Thickness: Comparison with Nerve Fiber Layer and Optic Nerve Head

      Glaucoma Diagnostic Accuracy of Ganglion Cell–Inner Plexiform Layer Thickness: Comparison with Nerve Fiber Layer and Optic Nerve Head

      Purpose To determine the diagnostic performance of macular ganglion cell–inner plexiform layer (GCIPL) thickness measured with the Cirrus high-definition optical coherence tomography (HD-OCT) ganglion cell analysis (GCA) algorithm (Carl Zeiss Meditec, Dublin, CA) to discriminate normal eyes and eyes with early glaucoma and to compare it with that of peripapillary retinal nerve fiber layer (RNFL) thickness and optic nerve head (ONH) measurements. Design Evaluation of diagnostic test or technology. Participants Fifty-eight patients with early glaucoma and 99 age-matched normal subjects. Methods Macular GCIPL and peripapillary RNFL thicknesses and ONH parameters were measured in each participant, and their diagnostic abilities ...

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    7. Macular Ganglion Cell–Inner Plexiform Layer: Automated Detection and Thickness Reproducibility with Spectral Domain–Optical Coherence Tomography in Glaucoma

      Macular Ganglion Cell–Inner Plexiform Layer: Automated Detection and Thickness Reproducibility with Spectral Domain–Optical Coherence Tomography in Glaucoma
      Purpose. To demonstrate the capability of SD-OCT to measure macular retinal ganglion cell–inner plexiform layer (GCIPL) thickness and to assess its reproducibility in glaucomatous eyes. Methods. Fifty-one glaucomatous eyes (26 mild, 11 moderate, 14 severe) of 51 patients underwent macular scanning using the Cirrus HD-OCT (Carl Zeiss Meditec, Dublin, CA) macula 200×200 acquisition protocol. Five scans were obtained on 5 days within 2 months. The ganglion cell analysis (GCA) algorithm was used to detect the macular GCIPL and to measure the thickness of the overall average, minimum, superotemporal, superior, superonasal, inferonasal, inferior, and inferotemporal GCIPL. The reproducibility of ...
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    8. Macular Ganglion Cell-Inner Plexiform Layer: Automated Detection and Thickness Reproducibility with Spectral-Domain Optical Coherence Tomography in Glaucoma

      Macular Ganglion Cell-Inner Plexiform Layer: Automated Detection and Thickness Reproducibility with Spectral-Domain Optical Coherence Tomography in Glaucoma
      Purpose. To demonstrate the capability of spectral domain OCT to measure the macular retinal ganglion cell layer-inner plexiform layer (GCIPL) thickness, and to assess its reproducibility in glaucomatous eyes. Methods. Fifty-one glaucomatous eyes (26 mild, 11 moderate and 14 severe) of 51 patients underwent macular scanning using the Cirrus HD-OCT (Carl Zeiss Meditec, Dublin, CA) Macular Cube 200x200 acquisition protocol. Five scans were obtained on five different days within two months. The Cirrus OCT ganglion cell analysis (GCA) algorithm was used to detect the macular GCIPL and measure the thickness of the overall average, minimum, superotemporal, superior, superonasal, inferonasal, inferior ...
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    9. Reproducibility of Peripapillary Retinal Nerve Fiber Layer Thickness and Optic Nerve Head Parameters Measured with Cirrus HD-OCT in Glaucomatous Eyes

      Reproducibility of Peripapillary Retinal Nerve Fiber Layer Thickness and Optic Nerve Head Parameters Measured with Cirrus HD-OCT in Glaucomatous Eyes

      PURPOSE. To assess the reproducibility of peripapillary retinal nerve fiber layer (RNFL) thickness and optic nerve head (ONH) parameters measured with CirrusTM HD-OCT in glaucomatous eyes. METHODS: Fifty-five glaucomatous eyes were included in the study. The optic disc cube 200x200 protocol was used to obtain three scans during the same visit to evaluate the intravisit reproducibility. One scan on four additional days within a two-month period of the first session was obtained to assess intervisit reproducibility. Intraclass correlation coefficients (ICC), coefficients of variation (COV) and test-retest standard deviation (TRT SD) were calculated for each RNFL and ONH parameter. The formula ...

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    10. Sensitivity and Specificity of Time-Domain versus Spectral-Domain Optical Coherence Tomography in Diagnosing Early to Moderate Glaucoma

      Purpose: To evaluate the sensitivity and specificity of measurements of retinal nerve fiber layer (RNFL) thickness in early to moderate glaucoma using Stratus time-domain and Cirrus spectral-domain optical coherence tomography (OCT; Carl Zeiss Meditec, Dublin, CA).Design: Evaluation of diagnostic test or technology.Participants: Fifty-four glaucoma subjects with early to moderate visual field defects and 50 age-matched normal subjects.Testing: Three peripapillary RNFL scans of 1 eye of each subject using Stratus and Cirrus OCT.Main Outcome Measures: Sensitivity and specificity of average, quadrant, and clock-hour RNFL thickness.Results: The average age±standard deviation in the normal and glaucoma groups ...
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    11. Comparison of Retinal Nerve Fiber Layer Measurements Using Time Domain and Spectral Domain Optical Coherent Tomography

      Comparison of Retinal Nerve Fiber Layer Measurements Using Time Domain and Spectral Domain Optical Coherent Tomography
      Purpose: To determine the agreement between peripapillary retinal nerve fiber layer (RNFL) thickness measurements from Stratus time domain optical coherence tomography (OCT) and Cirrus spectral domain OCT (Carl Zeiss Meditec, Dublin, CA) in normal subjects and subjects with glaucoma. Design: Evaluation of diagnostic test or technology. Participants: A total of 130 eyes from 130 normal subjects and subjects with glaucoma were analyzed. The subjects were divided into groups by visual field criteria: normal (n = 29), glaucoma suspect (n = 12), mild glaucoma (n = 41), moderate glaucoma (n = 18), and severe glaucoma (n = 30). Methods: Peripapillary RNFL thickness was measured with Stratus ...
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    12. Calibration of Fundus Images Using Spectral Domain Optical Coherence Tomography

      BACKGROUND AND OBJECTIVE Measurements performed on fundus images using current software are not accurate. Accurate measurements can be obtained only by calibrating a fundus camera using measurements between fixed retinal landmarks, such as the dimensions of the optic nerve, or by relying on a calibrated model eye provided by a reading center. However, calibrated spectral domain OCT (SD-OCT) could offer a convenient alternative method for the calibration of any fundus image. PATIENTS AND METHODS The ability to measure exact distances on SD-OCT fundus images was tested by measuring the distance between the center of the fovea and the optic nerve ...
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    1-12 of 12
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    Comparison of Retinal Nerve Fiber Layer Measurements Using Time Domain and Spectral Domain Optical Coherent Tomography Reproducibility of Peripapillary Retinal Nerve Fiber Layer Thickness and Optic Nerve Head Parameters Measured with Cirrus HD-OCT in Glaucomatous Eyes Macular Ganglion Cell-Inner Plexiform Layer: Automated Detection and Thickness Reproducibility with Spectral-Domain Optical Coherence Tomography in Glaucoma Macular Ganglion Cell–Inner Plexiform Layer: Automated Detection and Thickness Reproducibility with Spectral Domain–Optical Coherence Tomography in Glaucoma Glaucoma Diagnostic Accuracy of Ganglion Cell–Inner Plexiform Layer Thickness: Comparison with Nerve Fiber Layer and Optic Nerve Head Diagnostic Performance of Optical Coherence Tomography Ganglion Cell–Inner Plexiform Layer Thickness Measurements in Early Glaucoma Serial Spectral-Domain Optical Coherence Tomography Findings in Acute Retinal Pigment Epitheliitis and the Correlation to Visual Acuity Detection of glaucomatous optic neuropathy with spectral-domain optical coherence tomography: a retrospective training and validation deep-learning analysis 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