1. Articles from Michael D. Abràmoff

    1-24 of 55 1 2 3 »
    1. Multi-layer 3D Simultaneous Retinal OCT Layer Segmentation: Just-Enough Interaction for Routine Clinical Use

      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 prevents the use of quantitative retinal image analysis in clinical setting. In turn, the non-existence of reliable retinal layer segmentation methods substantially limits the use of precision medicine concepts in ...

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    2. 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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    3. 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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    4. Reproducibility of Retinal Thickness Measurements across Spectral-Domain Optical Coherence Tomography Devices using Iowa Reference Algorithm

      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 and Topcon2000, seven subjects with retinal diseases and four normal controls. METHOD: The Iowa Reference Algorithm measured total retinal thickness. Nonlinear model of total retinal thickness measurement comparisons was derived ...

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    5. Quantitative Analysis of Retinal OCT

      Quantitative Analysis of Retinal OCT

      Clinical acceptance of 3-D OCT retinal imaging brought rapid development of quantitative 3-D analysis of retinal layers, vascu-lature, retinal lesions as well as facilitated new research in retinal diseases. One of the cornerstones of many such analyses is segmentation and thickness quantification of retinal layers and the choroid, with an inherently 3-D simultaneous multi-layer LO-GISMOS (Layered Optimal Graph Image Segmentation for Multiple Objects and Surfaces) segmentation approach being extremely well suited for the task. Once retinal layers are segmented, regional thickness, brightness, or texture-based indices of individual layers can be easily determined and thus contribute to our understanding of retinal ...

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

      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 consisted of 420 OCT volumes with successful automated retinal nerve fiber layer (RNFL) segmentations obtained from our previously reported graph-based segmentation method and 270 volumes with failed segmentations. To evaluate ...

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    7. Evaluating Efficacy of Aflibercept in Refractory Exudative Age-Related Macular Degeneration With OCT Segmentation Volumetric Analysis

      Evaluating Efficacy of Aflibercept in Refractory Exudative Age-Related Macular Degeneration With OCT Segmentation Volumetric Analysis

      BACKGROUND AND OBJECTIVE: To use automated segmentation software to analyze spectral-domain optical coherence tomography (SD-OCT) scans and evaluate the effectiveness of aflibercept (Eylea; Regeneron, Tarrytown, NY) in the treatment of patients with exudative age-related macular degeneration (AMD) refractory to other treatments. PATIENTS AND METHODS: Retrospective chart review of 16 patients refractory to bevacizumab (Avastin; Genentech, South San Francisco, CA)/ranibizumab (Lucentis; Genentech, San Francisco, CA) treatment was conducted. Visual acuity, central foveal thickness (CFT), maximum fluid height, pigment epithelial detachment (PED) volume, sub-retinal fluid (SRF) volume, fluid-free time interval, and adverse effects were evaluated. Automated segmentation analysis was used to ...

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    8. Choroidal thickness maps from spectral domain and swept source optical coherence tomography: algorithmic versus ground truth annotation

      Choroidal thickness maps from spectral domain and swept source optical coherence tomography: algorithmic versus ground truth annotation

      Background/aims The purpose of the study was to create a standardised protocol for choroidal thickness measurements and to determine whether choroidal thickness measurements made on images obtained by spectral domain optical coherence tomography (SD-OCT) and swept source (SS-) OCT from patients with healthy retina are interchangeable when performed manually or with an automatic algorithm. Methods 36 grid cell measurements for choroidal thickness for each volumetric scan were obtained, which were measured for SD-OCT and SS-OCT with two methods on 18 eyes of healthy volunteers. Manual segmentation by experienced retinal graders from the Vienna Reading Center and automated segmentation on ...

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

      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 scan was acquired through a central pupil position, while subsequent scans were acquired through four peripheral pupil positions. The internal limiting membrane, the RPE, and Bruch's membrane were segmented ...

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

      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 manual segmentation. Differences were assessed to test the agreement between segmentation results of the same subject. Choroidal thickness was defined as the Euclidian distance between Bruch's membrane and the ...

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    11. Fast and memory-efficient LOGISMOS graph search for intraretinal layer segmentation of 3D macular OCT scans

      Fast and memory-efficient LOGISMOS graph search for intraretinal layer segmentation of 3D macular OCT scans

      Image segmentation is important for quantitative analysis of medical image data. Recently, our research group has introduced a 3-D graph search method which can simultaneously segment optimal interacting surfaces with respect to the cost function in volumetric images. Although it provides excellent segmentation accuracy, it is computationally demanding (both CPU and memory) to simultaneously segment multiple surfaces from large volumetric images. Therefore, we propose a new, fast, and memory-efficient graph search method for intraretinal layer segmentation of 3-D macular optical coherence tomograpy (OCT) scans. The key idea is to reduce the size of a graph by combining the nodes with ...

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    12. 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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    13. Optical density filters modeling media opacities cause decreased SD-OCT retinal layer thickness measurements with inter- and intra-individual variation

      Optical density filters modeling media opacities cause decreased SD-OCT retinal layer thickness measurements with inter- and intra-individual variation

      Purpose To assess the effect of media opacities on thickness measurements of the peripapillary retinal nerve fibre layer (pRNFL) and macular inner retinal layer (mIRL) performed with spectral-domain optical coherence tomography (SD-OCT) using a set of filters with known optical density. Methods Spectral-domain optical coherence tomography volume scans of the optic disc and the macular area were performed in 18 healthy volunteers, using Topcon-3DOCT-1000 Mark II. A set of five filters with optical density ranging from 0.04 to 0.69 was used. The correlation was calculated between the percentage change in thickness measurements (%ΔpRNFL and %ΔmIRL) and the change ...

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    14. 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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    15. 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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    16. Subvoxel Accurate Graph Search Using Non-Euclidean Graph Space.

      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 are ignored. We generalize the graph to non-Euclidean space by allowing non-equidistant spacing between nodes, so that subvoxel accurate segmentation is achievable. Because the number of nodes and edges in ...

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    17. Three-dimensional automated choroidal volume assessment on standard spectral-domain optical coherence tomography and correlation with the level of diabetic macular edema

      Three-dimensional automated choroidal volume assessment on standard spectral-domain optical coherence tomography and correlation with the level of diabetic macular edema

      Purpose To measure choroidal thickness on spectral-domain optical coherence tomography (SD-OCT) images using automated algorithms and to correlate choroidal pathology with retinal changes due to diabetic macular edema (DME). Design Post-hoc analysis of multicenter clinical trial baseline data. Methods SD-OCT raster scans/fluorescein angiograms were obtained from 284 treatment naïve eyes of 142 patients with clinically significant DME and from 20 controls. Three-dimensional (3D) SD-OCT images were evaluated by a certified independent reading center analyzing retinal changes associated with diabetic retinopathy. Choroidal thicknesses were analyzed using a fully automated algorithm. Angiograms were assessed manually. Multiple endpoint correction according to ...

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

      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 a novel graphtheoretic method for multi-surface multi-field co-segmentation of intraretinal layers, assuring consistent segmentation of the fields across the overlapped areas. After 2D en-face alignment, all the fields are segmented ...

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    19. Quantifying disrupted outer retina-subretinal layer in SD-OCT images in choroidal neovascularization

      Quantifying disrupted outer retina-subretinal layer in SD-OCT images in choroidal neovascularization

      Purpose: To report a fully automated method to identify and quantify the thickness of the outer retinal-subretinal (ORSR) layer from clinical spectral-domain optical coherence tomography (SD-OCT) scans of choroidal neovascularization (CNV) due to exudative age-related macular degeneration (e-AMD). Methods: 23 Subjects with CNV met eligibility. Volumetric SD-OCT scans of 23 eyes were obtained (Zeiss Cirrus, 200×200×1024 voxels). In a subset of eyes, scans were repeated. OCT volumes were analyzed using our standard parameters and using a 3D graph-search approach with an adaptive cost function. A retinal specialist graded the segmentation as generally accurate, local segmentation inaccuracies, or failure ...

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    20. Thickness Mapping of Eleven Retinal Layers in Normal Eyes Using Spectral Domain Optical Coherence Tomography

      Thickness Mapping of Eleven Retinal Layers in Normal Eyes Using Spectral Domain Optical Coherence Tomography

      Purpose. This study was conducted to determine the thickness map of eleven retinal layers in normal subjects by spectral domain optical coherence tomography (SD-OCT) and evaluate their association with sex and age. Methods. Mean regional retinal thickness of 11 retinal layers were obtained by automatic three-dimensional diffusion-map-based method in 112 normal eyes of 76 Iranian subjects. Results. The thickness map of central foveal area in layer 1, 3, and 4 displayed the minimum thickness (P<0.005 for all). Maximum thickness was observed in nasal to the fovea of layer 1 (P<0.001) and in a circular pattern in ...

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    21. 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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    22. Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

      Optical Coherence Tomography Noise Reduction Using Anisotropic Local Bivariate Gaussian Mixture Prior in 3D Complex Wavelet Domain

      In this paper, MMSE estimator is employed for noise-free 3D OCT data recovery in 3D complex wavelet domain. Since the proposed distribution for noise-free data plays a key role in the performance of MMSE estimator, a priori distribution for the pdf of noise-free 3D complex wavelet coefficients is proposed which is able to model the main statistical properties of wavelets. We model the coefficients with a mixture of two bivariate Gaussian pdfs with local parameters which are able to capture the heavy-tailed property and inter- and intrascale dependencies of coefficients. In addition, based on the special structure of OCT images ...

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    23. 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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    24. 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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    1-24 of 55 1 2 3 »
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    1. (55 articles) University of Iowa
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