1. Articles from Mona K. Garvin

    1-24 of 36 1 2 »
    1. Utility of Spectral-Domain Optical Coherence Tomography in Differentiating Papilledema From Pseudopapilledema: A Prospective Longitudinal Study

      Utility of Spectral-Domain Optical Coherence Tomography in Differentiating Papilledema From Pseudopapilledema: A Prospective Longitudinal Study

      Background: Prospective and longitudinal studies assessing the utility of spectral-domain optical coherence tomography (SD-OCT) to differentiate papilledema from pseudopapilledema are lacking. We studied the sensitivity and specificity of baseline and longitudinal changes in SD-OCT parameters with 3D segmentation software to distinguish between papilledema and pseudopapilledema in a cohort of patients referred for evaluation of undiagnosed optic disc elevation. Methods: Fifty-two adult patients with optic disc elevation were enrolled in a prospective longitudinal study. A diagnosis of papilledema was made when there was a change in the appearance of the optic disc elevation on fundus photographs as noted by an independent ...

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    2. A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input

      A Deep-Learning Approach for Automated OCT En-Face Retinal Vessel Segmentation in Cases of Optic Disc Swelling Using Multiple En-Face Images as Input

      Purpose : In cases of optic disc swelling, segmentation of projected retinal blood vessels from optical coherence tomography (OCT) volumes is challenging due to swelling-based shadowing artifacts. Based on our hypothesis that simultaneously considering vessel information from multiple projected retinal layers can substantially increase vessel visibility, in this work, we propose a deep-learning-based approach to segment vessels involving the simultaneous use of three OCT en-face images as input. Methods : A human expert vessel tracing combining information from OCT en-face images of the retinal pigment epithelium (RPE), inner retina, and total retina as well as a registered fundus image served as the ...

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    3. Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography

      Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography

      Microvascular changes are one of the early symptoms of retinal diseases. Recently developed optical coherence tomography angiography (OCTA) technology allows visualization and analysis of the retinal microvascular network in a non-invasive way. However, automated analysis of microvascular changes in OCTA is not a trivial task. Current approaches often attempt to directly segment the microvasculature. These approaches generally have problems in cases of poor image quality and limited visibility of the vasculature. Evaluating the quality of the results is also challenging because of the difficulty of manually tracing the microvasculature, especially in cases of low image quality or with images with ...

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

      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+IPL) layers were cosegmented and partitioned into 52 sectors matching HVF 24-2 test locations. The Wilcoxon rank sum test was applied to test correlation R , root mean square error (RMSE ...

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

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

      Bruch’s 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 in individual B-scans, in this work, we propose a machine-learning graph-based approach for true 3D segmentation of BMO from glaucomatous SD-OCT volumes. The problem is formulated as an optimization ...

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    6. The Pattern of Visual Fixation Eccentricity and Instability in Optic Neuropathy and Its Spatial Relationship to Retinal Ganglion Cell Layer Thickness

      The Pattern of Visual Fixation Eccentricity and Instability in Optic Neuropathy and Its Spatial Relationship to Retinal Ganglion Cell Layer Thickness

      Purpose : The purpose of this study was to assess whether clinically useful measures of fixation instability and eccentricity can be derived from retinal tracking data obtained during optical coherence tomography (OCT) in patients with optic neuropathy (ON) and to develop a method for relating fixation to the retinal ganglion cell complex (GCC) thickness. Methods : Twenty-nine patients with ON underwent macular volume OCT with 30 seconds of confocal scanning laser ophthalmoscope (cSLO)-based eye tracking during fixation. Kernel density estimation quantified fixation instability and fixation eccentricity from the distribution of fixation points on the retina. Preferred ganglion cell layer loci (PGCL ...

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    7. Combined use of high-density and volumetric optical coherence tomography for the segmentation of neural canal opening in cases of optic nerve edema

      Combined use of high-density and volumetric optical coherence tomography for the segmentation of neural canal opening in cases of optic nerve edema

      In cases of optic-nerve-head edema, the presence of the swelling reduces the visibility of the underlying neural canal opening (NCO) within spectral-domain optical coherence tomography (SD-OCT) volumes. Consequently, traditional SD-OCT-based NCO segmentation methods often overestimate the size of the NCO. The visibility of the NCO can be improved using high-definition 2D raster scans, but such scans do not provide 3D contextual image information. In this work, we present a semi-automated approach for the segmentation of the NCO in cases of optic disc edema by combining image information from volumetric and high-definition raster SD-OCT image sequences. In particular, for each subject ...

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

      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 - OCT volume. Three inregion cost functions are designed using a random forest classifier corresponding to three regions of cup , rim, and background. Next, the volumes are resampled to create radial ...

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    9. Automated 3D Segmentation of Intraretinal Surfaces in SD-OCT Volumes in Normal and Diabetic Mice

      Automated 3D Segmentation of Intraretinal Surfaces in SD-OCT Volumes in Normal and Diabetic Mice

      Purpose: To describe an adaptation of an existing graph-theoretic method (initially developed for human optical coherence tomography [ OCT ] images) for the three-dimensional ( 3D ) automated segmentation of 10 intraretinal surfaces in mice scans, and assess the accuracy of the method and the reproducibility of thickness measurements. Methods: Ten intraretinal surfaces were segmented in repeat spectral domain ( SD )- OCT volumetric images acquired from normal ( n = 8) and diabetic ( n = 10) mice . The accuracy of the method was assessed by computing the border position errors of the automated segmentation with respect to manual tracings obtained from two experts. The reproducibility was statistically assessed ...

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

      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 neural canal opening seen in spectral-domain optical coherence tomography volumes is an example of a “hole” embedded with multiple surrounding surfaces. Segmentation approaches that rely on finding the surfaces alone ...

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    11. 3D graph-based automated segmentation of corneal layers in anterior-segment optical coherence tomography images of mice

      3D graph-based automated segmentation of corneal layers in anterior-segment optical coherence tomography images of mice

      Anterior segment optical coherence tomography (AS-OCT) is a non-invasive imaging modality that allows for the quantitative assessment of corneal thicknesses. Automated approaches for these measurements are not readily available and therefore measurements are often obtained manually. While graph-based approaches that enable the optimal simultaneous segmentation of multiple 3D surfaces have been proposed and applied to 3D optical coherence tomography volumes of the back of the eye, such approaches have not been applied for the segmentation of the corneal surfaces. In this work we propose adapting this graph-based method for the automated 3D segmentation of three corneal surfaces in AS-OCT images ...

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    12. A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes

      A combined machine-learning and graph-based framework for the segmentation of retinal surfaces in SD-OCT volumes

      Optical coherence tomography is routinely used clinically for the detection and management of ocular diseases as well as in research where the studies may involve animals. This routine use requires that the developed automated segmentation methods not only be accurate and reliable, but also be adaptable to meet new requirements. We have previously proposed the use of a graph-theoretic approach for the automated 3-D segmentation of multiple retinal surfaces in volumetric human SD-OCT scans. The method ensures the global optimality of the set of surfaces with respect to a cost function. Cost functions have thus far been typically designed by ...

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

      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 HD-OCT machine (Carl Zeiss Meditec, Inc., Dublin, CA)) were acquired within a 4-month period from one eye of the 56 patients. Retinal angle correction in B-scans was accomplished by adjusting ...

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    14. Effect of Age on Individual Retinal Layer Thickness in Normal Eyes as Measured with Spectral-Domain Optical Coherence Tomography

      Effect of Age on Individual Retinal Layer Thickness in Normal Eyes as Measured with Spectral-Domain Optical Coherence Tomography

      Purpose. To determine the effect of age on the thickness of individual retinal layers, measured with spectral-domain optical coherence tomography (SD-OCT), in a population of healthy Caucasians. Methods. One hundred and twenty subjects with an age ranging between 18 and 81 years were examined with SD-OCT (Topcon, Mark II). Mean layer thickness was calculated for 7 retinal layers, in the fovea (region 1 of the 9 ETDRS regions), in the pericentral ring (ETDRS regions 2 to 5), and the peripheral ring (ETDRS region 6 to 9) following automated segmentation using the Iowa Reference Algorithm. In addition, mean peripapillary retinal nerve ...

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    15. Multimodal segmentation of optic disc and cup from stereo fundus and SD-OCT images

      Multimodal segmentation of optic disc and cup from stereo fundus and SD-OCT images

      Glaucoma is one of the major causes of blindness worldwide. One important structural parameter for the diagnosis and management of glaucoma is the cup-to-disc ratio (CDR), which tends to become larger as glaucoma progresses. While approaches exist for segmenting the optic disc and cup within fundus photographs, and more recently, within spectral-domain optical coherence tomography (SD-OCT) volumes, no approaches have been reported for the simultaneous segmentation of these structures within both modalities combined. In this work, a multimodal pixel-classification approach for the segmentation of the optic disc and cup within fundus photographs and SD-OCT volumes is presented. In particular, after ...

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    16. Extending the XNAT archive tool for image and analysis management in ophthalmology research

      Extending the XNAT archive tool for image and analysis management in ophthalmology research

      In ophthalmology, various modalities and tests are utilized to obtain vital information on the eye’s structure and function. For example, optical coherence tomography (OCT) is utilized to diagnose, screen, and aid treatment of eye diseases like macular degeneration or glaucoma. Such data are complemented by photographic retinal fundus images and functional tests on the visual field. DICOM isn’t widely used yet, though, and frequently images are encoded in proprietary formats. The eXtensible Neuroimaging Archive Tool (XNAT) is an open-source NIH-funded framework for research PACS and is in use at the University of Iowa for neurological research applications. Its ...

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    17. Automated 3D region-based volumetric estimation of optic disc swelling in papilledema using spectral-domain optical coherence tomography

      Automated 3D region-based volumetric estimation of optic disc swelling in papilledema using spectral-domain optical coherence tomography

      The six-stage Frisén scale is a qualitative and subjective method for assessing papilledema (optic disc swelling due to raised intracranial pressure) using fundus photographs. The recent introduction of spectral-domain optical coherence tomography (SD-OCT) presents a promising alternative to enable the 3-D quantitative estimation of papilledema. In this work, we propose an automated region-based volumetric estimation of the degree of papilledema from SD-OCT. After using a custom graph-based approach to segment the surfaces of the swollen optic nerve head, the volumes of the nasal, superior, temporal, and inferior regions are computed. Using a dataset of 70 SD-OCT optic-nerve-head (ONH) SD-OCT ...

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    18. Optimal Multiple Surface Segmentation With Shape and Context Priors

      Optimal Multiple Surface Segmentation With Shape and Context Priors

      Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary evidence, large object deformations, and mutual influence between adjacent objects. This paper reports a novel approach to multi-object segmentation that incorporates both shape and context prior knowledge in a 3-D graph-theoretic framework to help overcome the stated challenges. We employ an arc-based graph representation to incorporate a wide spectrum of prior information through pair-wise energy terms. In particular, a shape-prior term is used to penalize local shape changes and a context-prior term is used to penalize local surface-distance changes from ...

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    19. Multimodal Retinal Vessel Segmentation from Spectral-Domain Optical Coherence Tomography and Fundus Photography

      Multimodal Retinal Vessel Segmentation from Spectral-Domain Optical Coherence Tomography and Fundus Photography

      Segmenting retinal vessels in optic nerve head (ONH) centered spectral-domain optical coherence tomography (SD-OCT) volumes is particularly challenging due to the projected neural canal opening (NCO) and relatively low visibility in the ONH center. Color fundus photographs provide a relatively high vessel contrast in the region inside the NCO, but have not been previously used to aid the SD-OCT vessel segmentation process. Thus, in this paper, we present two approaches for the segmentation of retinal vessels in SD-OCT volumes that each take advantage of complimentary information from fundus photographs. In the first approach (referred to as the registeredfundus vessel segmentation ...

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

      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) analysis was performed; the mean regional retinal ganglion cell layer thickness (68 regions), nerve fiber layer (NFL) thickness (120 regions), and ONH rim area (12 wedge-shaped regions) were determined. Maps ...

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    21. Automated Quantification of Volumetric Optic Disc Swelling in Papilledema Using Spectral-Domain Optical Coherence Tomography

      Automated Quantification of Volumetric Optic Disc Swelling in Papilledema Using Spectral-Domain Optical Coherence Tomography

      Purpose: To develop an automated method for the quantification of volumetric optic disc swelling in papilledema subjects using spectral-domain optical coherence tomography (SD-OCT) and to determine the extent that such volumetric measurements correlate with Frisén scale grades (from fundus photographs) and 2-D peripapillary retinal-nerve-fiber-layer (RNFL) and total-retinal (TR) thickness measurements from SD-OCT. Methods: A custom image-analysis algorithm was developed to obtain peripapillary circular RNFL thickness, TR thickness, and TR volume measurements from SD-OCT volumes of subjects with papilledema. In addition, peripapillary RNFL thickness measures from the commercially available Zeiss SD-OCT machine were obtained. Expert Frisén scale grades were independently obtained ...

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    22. Parallel graph search: application to intraretinal layer segmentation of 3D macular OCT scans

      Parallel graph search: application to intraretinal layer segmentation of 3D macular OCT scans

      Image segmentation is of paramount importance for quantitative analysis of medical image data. Recently, a 3-D graph search method which can detect globally optimal interacting surfaces with respect to the cost function of volumetric images has been introduced, and its utility demonstrated in several application areas. Although the method provides excellent segmentation accuracy, its limitation is a slow processing speed when many surfaces are simultaneously segmented in large volumetric datasets. Here, we propose a novel method of parallel graph search, which overcomes the limitation and allows the quick detection of multiple surfaces. To demonstrate the obtained performance with respect to ...

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    23. Registration of 3D spectral OCT volumes combining ICP with a graph-based approach

      Registration of 3D spectral OCT volumes combining ICP with a graph-based approach

      The introduction of spectral Optical Coherence Tomography (OCT) scanners has enabled acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D-OCT is used to detect and manage eye diseases such as glaucoma and age-related macular degeneration. To follow-up patients over time, image registration is a vital tool to enable more precise, quantitative comparison of disease states. In this work we present a 3D registrationmethod based on a two-step approach. In the first step we register both scans in the XY domain using an Iterative Closest Point (ICP) based algorithm. This algorithm is applied to vessel segmentations obtained from ...

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    24. Parallel graph search: application to intraretinal layer segmentation of 3-D macular OCT scans

      Parallel graph search: application to intraretinal layer segmentation of 3-D macular OCT scans

      Image segmentation is of paramount importance for quantitative analysis of medical image data. Recently, a 3-D graph search method which can detect globally optimal interacting surfaces with respect to the cost function of volumetric images has been introduced, and its utility demonstrated in several application areas. Although the method provides excellent segmentation accuracy, its limitation is a slow processing speed when many surfaces are simultaneously segmented in large volumetric datasets. Here, we propose a novel method of parallel graph search, which overcomes the limitation and allows the quick detection of multiple surfaces. To demonstrate the obtained performance with respect to ...

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    1. (36 articles) University of Iowa
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