1. Young H. Kwon

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    1. Mentioned In 18 Articles

    2. Optical Coherence Tomography Analysis Based Prediction of Humphrey 24-2 Visual Field Thresholds in Patients With Glaucoma

      Explore IOVS Journal Ophthalmology
      Optical Coherence Tomography Analysis Based Prediction of Humphrey 24-2 Visual Field Thresholds in Patients With Glaucoma
      Purpose : A pilot study showed that prediction of individual Humphrey 24-2 visual field (HVF 24-2) sensitivity thresholds from optical coherence tomography (OCT) image analysis is possible. We evaluate performance of an improved approach as well as 3 other predictive algorithms on a new, fully independent set of glaucoma subjects. Methods : Subjects underwent HVF 24-2 and 9-field OCT (Heidelberg Spectralis) testing. Nerve fiber (NFL), and ganglion cell and inner plexiform (GCL ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    3. A Machine-Learning Graph-Based Approach for 3D Segmentation of Bruch’s Membrane Opening from Glaucomatous SD-OCT Volumes

      Explore Medical Image Analysis Ophthalmology
      A Machine-Learning Graph-Based Approach for 3D Segmentation of Bruch’s Membrane Opening from Glaucomatous SD-OCT Volumes
      Bruchs membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Measuring this structural parameter requires identification of BMO locations within spectral domain-optical coherence tomography (SD-OCT) volumes. While most automated approaches for segmentation of the BMO either segment the 2D projection of BMO points or identify BMO points ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    4. Multimodal Segmentation of Optic Disc and Cup from SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach

      Explore IEEE Xplore Ophthalmology
      Multimodal Segmentation of Optic Disc and Cup from SD-OCT and Color Fundus Photographs Using a Machine-Learning Graph-Based Approach
      In this work, a multimodal approach is proposed to use the complementary information from fundus photographs and spectral domain optical coherence tomography ( SD - OCT ) volumes in order to segment the optic disc and cup boundaries. The problem is formulated as an optimization problem where the optimal solution is obtained using a machine-learning theoretical graph-based method. In particular, first the fundus photograph is registered to the 2D projection of the SD ...
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      Mentions: Michael D. Abràmoff University of Iowa Kyungmoo Lee

    5. Automated 3D segmentation of multiple surfaces with a shared hole: segmentation of the neural canal opening in SD-OCT volumes

      Explore Home - Springer
      Automated 3D segmentation of multiple surfaces with a shared hole: segmentation of the neural canal opening in SD-OCT volumes
      The need to segment multiple interacting surfaces is a common problem in medical imaging and it is often assumed that such surfaces are continuous within the confines of the region of interest. However, in some application areas, the surfaces of interest may contain a shared hole in which the surfaces no longer exist and the exact location of the hole boundary is not known a priori . The boundary of the ...
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      Mentions: Michael D. Abràmoff University of Iowa Young H. Kwon

    6. Multi-Surface and Multi-Field Co-Segmentation of 3-D Retinal Optical Coherence Tomography

      Explore IEEE Xplore Ophthalmology
      Multi-Surface and Multi-Field Co-Segmentation of 3-D Retinal Optical Coherence Tomography
      When segmenting intraretinal layers from multiple optical coherence tomography (OCT) images forming a mosaic or a set of repeated scans, it is attractive to exploit the additional information from the overlapping areas rather than discarding it as redundant, especially in low contrast and noisy images. However, it is currently not clear how to effectively combine the multiple information sources available in the areas of overlap. In this paper, we propose ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    8. Adjustment of the Retinal Angle in SD-OCT of Glaucomatous Eyes Provides Better Intervisit Reproducibility of Peripapillary RNFL Thickness

      Explore iovs.org Ophthalmology
      Adjustment of the Retinal Angle in SD-OCT of Glaucomatous Eyes Provides Better Intervisit Reproducibility of Peripapillary RNFL Thickness
      Purpose: To report an automated method for adjustment of the retinal angle in spectral-domain optical coherence tomography (SD-OCT) and compare its intervisit reproducibility of the peripapillary retinal nerve fiber layer (RNFL) thicknesses of glaucomatous eyes to that obtained by the Cirrus algorithm. Methods: Fifty-six glaucoma and glaucoma suspect subjects were repeatedly imaged, and optic nerve head (ONH)-centered OCT image volumes (200 200 1024 voxels, 6 6 2 mm3, CirrusTM ...
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      Mentions: Carl Zeiss Meditec Michael D. Abràmoff University of Iowa

    10. Distribution of Damage to the Entire Retinal Ganglion Cell PathwayQuantified Using Spectral-Domain Optical Coherence Tomography Analysis in Patients With Glaucoma

      Explore JAMA Network Ophthalmology
      Distribution of Damage to the Entire Retinal Ganglion Cell PathwayQuantified Using Spectral-Domain Optical Coherence Tomography Analysis in Patients With Glaucoma
      Objectives To test the hypothesis that the amount and distribution of glaucomatous damage along the entire retinal ganglion cell–axonal complex (RGC-AC) can be quantified and to map the RGC-AC connectivity in early glaucoma using automated image analysis of standard spectral-domain optical coherence tomography. Methods Spectral-domain optical coherence tomography volumes were obtained from 116 eyes in 58 consecutive patients with glaucoma or suspected glaucoma. Layer and optic nerve head (ONH ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    11. Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes

      Explore SPIE Digital Library Ophthalmology
      Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes
      While efficient graph-theoretic approaches exist for the optimal (with respect to a cost function) and simultaneous segmentation of multiple surfaces within volumetric medical images, the appropriate design of cost functions remains an important challenge. Previously proposed methods have used simple cost functions or optimized a combination of the same, but little has been done to design cost functions using learned features from a training set, in a less biased fashion ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    14. Automated Segmentation of Neural Canal Opening and Optic Cup in 3-D Spectral Optical Coherence Tomography Volumes of the Optic Nerve Head

      Explore iovs.org Ophthalmology
      Automated Segmentation of Neural Canal Opening and Optic Cup in 3-D Spectral Optical Coherence Tomography Volumes of the Optic Nerve Head
      Purpose: To develop an automated approach for segmenting the neural canal opening (NCO) and cup at the level of retinal pigment epithelium (RPE)/Bruch's membrane (BM) complex in spectral-domain optical coherence tomography (SD-OCT) volumes. To investigate the correspondence and discrepancy of the NCO-based metrics and clinical disc margin on fundus photographs in glaucoma subjects. Methods: SD-OCT scans (CirrusTM HD-OCT) and corresponding stereo fundus photographs (Nidek 3Dx) of the optic ...
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      Mentions: Nidek Carl Zeiss Meditec Michael D. Abràmoff

    15. Methods and systems for optic nerve head segmentation

      Explore uspto.gov Ophthalmology , Patents
      Methods and systems for optic nerve head segmentation
      A method of classifying an optic nerve cup and rim of an eye from a retinal image comprising receiving a retinal image, determining a feature vector for a candidate pixel in the retinal image, and classifying the candidate pixel as a cup pixel or a rim pixel based on the feature vector using a trained classifier. The retinal image can be a stereo pair, the retinal image can be color ...
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      Mentions: Michael D. Abràmoff University of Iowa Young H. Kwon
    17. 1-15 of 18 1 2 »
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  4. About Young H. Kwon

    Young H. Kwon

    Young H. Kwon, MD, is a professor of Ophthalmology in the Department of Ophthalmology and Visual Sciences at the University of Iowa.

  5. Related Topics

    1. 3-D segmentation of the rim and cup in spectral-domain optical coherence tomography volumes of the optic nerve head
      18 articles also mentioned Michael D. Abràmoff
    2. Automated Segmentation of the Cup and Rim from Spectral Domain OCT of the Optic Nerve Head
      3 articles also mentioned Carl Zeiss Meditec