1. Kyungmoo Lee

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    1. Mentioned In 33 Articles

    2. Multi-layer 3D Simultaneous Retinal OCT Layer Segmentation: Just-Enough Interaction for Routine Clinical Use

      Explore Home - Springer Ophthalmology
      Multi-layer 3D Simultaneous Retinal OCT Layer Segmentation: Just-Enough Interaction for Routine Clinical Use
      All current fully automated retinal layer segmentation methods fail in some subset of clinical 3D Optical Coherence Tomography (OCT) datasets, especially in the presence of appearance-modifying retinal diseases like Age-related Macular Degeneration (AMD), Diabetic Macular Edema (DME), and others. In the presence of local or regional failures, the only current remedy is to edit the obtained segmentation in a slice-by-slice manner. This is a very tedious and time-demanding process, which ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    3. 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

    4. Reproducibility of Retinal Thickness Measurements across Spectral-Domain Optical Coherence Tomography Devices using Iowa Reference Algorithm

      Explore arxiv.org Ophthalmology
      Reproducibility of Retinal Thickness Measurements across Spectral-Domain Optical Coherence Tomography Devices using Iowa Reference Algorithm
      PURPOSE: Establishing and obtaining consistent quantitative indices of retinal thickness from a variety of clinically used Spectral-Domain Optical Coherence Tomography scanners. DESIGN: Retinal images from five Spectral-Domain Optical Coherence Tomography scanners were used to determine total retinal thickness with scanner-specific correction factors establishing consistency of thickness measurement across devices. PARTICIPANTS: 55 Fovea-centered Spectral-Domain Optical Coherence Tomography volumes from eleven subjects were analyzed, obtained from Cirrus HD-OCT, RS-3000, Heidelberg Spectralis, RTVue ...
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      Mentions: Medical University of Vienna Michael D. Abràmoff Ursula Schmidt-Erfurth

    5. Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Image

      Explore TVST Journal Ophthalmology
      Automated Segmentability Index for Layer Segmentation of Macular SD-OCT Image
      Purpose : To automatically identify which spectral-domain optical coherence tomography (SD-OCT) scans will provide reliable automated layer segmentations for more accurate layer thickness analyses in population studies. Methods : Six hundred ninety macular SD-OCT image volumes (6.0 6.0 2.3 mm 3 ) were obtained from one eyes of 690 subjects (74.6 9.7 [mean SD] years, 37.8% of males) randomly selected from the population-based Rotterdam Study. The dataset ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    6. Characterizing the Impact of Off-Axis Scan Acquisition on the Reproducibility of Total Retinal Thickness Measurements in SDOCT Volumes

      Explore TVST Journal Ophthalmology
      Characterizing the Impact of Off-Axis Scan Acquisition on the Reproducibility of Total Retinal Thickness Measurements in SDOCT Volumes
      Purpose : Off-axis acquisition of spectral domain optical coherence tomography (SDOCT) images has been shown to increase total retinal thickness (TRT) measurements. We analyzed the reproducibility of TRT measurements obtained using either the retinal pigment epithelium (RPE) or Bruch's membrane as reference surfaces in off-axis scans intentionally acquired through multiple pupil positions. Methods : Five volumetric SDOCT scans of the macula were obtained from one eye of 25 normal subjects. One ...
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      Mentions: Michael D. Abràmoff University of Iowa Kyungmoo Lee

    7. Validity of Automated Choroidal Segmentation in SS-OCT and SD-OCT

      Explore IOVS Journal Ophthalmology
      Validity of Automated Choroidal Segmentation in SS-OCT and SD-OCT
      Purpose. To evaluate the validity of a novel fully automated three-dimensional (3D) method capable of segmenting the choroid from two different optical coherence tomography scanners: swept-source OCT (SS-OCT) and spectral-domain OCT (SD-OCT). Methods. One hundred eight subjects were imaged using SS-OCT and SD-OCT. A 3D method was used to segment the choroid and quantify the choroidal thickness along each A-scan. The segmented choroidal posterior boundary was evaluated by comparing to ...
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      Mentions: Michael D. Abràmoff University of Iowa Milan Sonka

    9. 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

    10. Subvoxel Accurate Graph Search Using Non-Euclidean Graph Space.

      Explore PLoS ONE
      Subvoxel Accurate Graph Search Using Non-Euclidean Graph Space.
      Graph search is attractive for the quantitative analysis of volumetric medical images, and especially for layered tissues, because it allows globally optimal solutions in low-order polynomial time. However, because nodes of graphs typically encode evenly distributed voxels of the volume with arcs connecting orthogonally sampled voxels in Euclidean space, segmentation cannot achieve greater precision than a single unit, i.e. the distance between two adjoining nodes, and partial volume effects ...
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      Mentions: Michael D. Abràmoff University of Iowa Kyungmoo Lee

    11. 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

    12. Reproducibility of Diabetic Macular Edema estimates from SD-OCT is affected by the choice of image analysis algorithm

      Explore iovs.org Ophthalmology
      Reproducibility of Diabetic Macular Edema estimates from SD-OCT is affected by the choice of image analysis algorithm
      Purpose: To evaluate the inter-session repeatability of retinal thickness measurements in patients with diabetic macular edema (DME) using the Heidelberg Spectralis OCT algorithm and a publicly available, 3D graph search based multilayer OCT segmentation algorithm, the Iowa Reference Algorithm. Methods: 30 eyes from 21 patients diagnosed with clinically significant DME were included and underwent consecutive, registered macula-centered spectral domain optical coherence scans (Heidelberg Spectralis). The OCT scans were segmented into ...
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      Mentions: Heidelberg Engineering Michael D. Abràmoff University of Iowa
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  4. About Kyungmoo Lee

    Kyungmoo Lee is with the Department of Ophthalmology and Visual Sciences at the University of Iowa.

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    2. Automated Segmentation of the Cup and Rim from Spectral Domain OCT of the Optic Nerve Head
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