1. Articles from Jerry L. Prince

    1-16 of 16
    1. Improving graph-based OCT segmentation for severe pathology in retinitis pigmentosa patients

      Improving graph-based OCT segmentation for severe pathology in retinitis pigmentosa patients

      Three dimensional segmentation of macular optical coherence tomography (OCT) data of subjects with retinitis pigmentosa (RP) is a challenging problem due to the disappearance of the photoreceptor layers, which causes algorithms developed for segmentation of healthy data to perform poorly on RP patients. In this work, we present enhancements to a previously developed graph-based OCT segmentation pipeline to enable processing of RP data. The algorithm segments eight retinal layers in RP data by relaxing constraints on the thickness and smoothness of each layer learned from healthy data. Following from prior work, a random forest classifier is first trained on the ...

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    2. Collaborative SDOCT segmentation and analysis software

      Collaborative SDOCT segmentation and analysis software

      Spectral domain optical coherence tomography (SDOCT) is routinely used in the management and diagnosis of a variety of ocular diseases. This imaging modality also finds widespread use in research, where quantitative measurements obtained from the images are used to track disease progression. In recent years, the number of available scanners and imaging protocols grown and there is a distinct absence of a unified tool that is capable of visualizing, segmenting, and analyzing the data. This is especially noteworthy in longitudinal studies, where data from older scanners and/or protocols may need to be analyzed. Here, we present a graphical user ...

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    3. Longitudinal analysis of mouse SDOCT volumes

      Longitudinal analysis of mouse SDOCT volumes

      Spectral-domain optical coherence tomography (SDOCT), in addition to its routine clinical use in the diagnosis of ocular diseases, has begun to fund increasing use in animal studies. Animal models are frequently used to study disease mechanisms as well as to test drug efficacy. In particular, SDOCT provides the ability to study animals longitudinally and non-invasively over long periods of time. However, the lack of anatomical landmarks makes the longitudinal scan acquisition prone to inconsistencies in orientation. Here, we propose a method for the automated registration of mouse SDOCT volumes. The method begins by accurately segmenting the blood vessels and the ...

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    4. Voxel based morphometry in optical coherence tomography: validation and core findings

      Voxel based morphometry in optical coherence tomography: validation and core findings

      Optical coherence tomography (OCT) of the human retina is now becoming established as an important modality for the detection and tracking of various ocular diseases. Voxel based morphometry (VBM) is a long standing neuroimaging analysis technique that allows for the exploration of the regional differences in the brain. There has been limited work done in developing registration based methods for OCT, which has hampered the advancement of VBM analyses in OCT based population studies. Following on from our recent development of an OCT registration method, we explore the potential benefits of VBM analysis in cohorts of healthy controls (HCs) and ...

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    5. Simultaneous segmentation of retinal surfaces and microcystic macular edema in SDOCT volumes

      Simultaneous segmentation of retinal surfaces and microcystic macular edema in SDOCT volumes

      Optical coherence tomography (OCT) is a noninvasive imaging modality that has begun to find widespread use in retinal imaging for the detection of a variety of ocular diseases. In addition to structural changes in the form of altered retinal layer thicknesses, pathological conditions may also cause the formation of edema within the retina. In multiple sclerosis, for instance, the nerve fiber and ganglion cell layers are known to thin. Additionally, the formation of pseudocysts called microcystic macular edema (MME) have also been observed in the eyes of about 5% of MS patients, and its presence has been shown to be ...

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    6. Combined registration and motion correction of longitudinal retinal OCT data

      Combined registration and motion correction of longitudinal retinal OCT data

      Optical coherence tomography (OCT) has become an important modality for examination of the eye. To measure layer thicknesses in the retina, automated segmentation algorithms are often used, producing accurate and reliable measurements. However, subtle changes over time are difficult to detect since the magnitude of the change can be very small. Thus, tracking disease progression over short periods of time is difficult. Additionally, unstable eye position and motion alter the consistency of these measurements, even in healthy eyes. Thus, both registration and motion correction are important for processing longitudinal data of a specific patient. In this work, we propose a ...

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    7. Optical coherence tomography reflects brain atrophy in multiple sclerosis: A four-year study

      Optical coherence tomography reflects brain atrophy in multiple sclerosis: A four-year study

      Objective The aim of this work was to determine whether atrophy of specific retinal layers and brain substructures are associated over time, in order to further validate the utility of optical coherence tomography (OCT) as an indicator of neuronal tissue damage in patients with multiple sclerosis (MS). Methods Cirrus high-definition OCT (including automated macular segmentation) was performed in 107 MS patients biannually (median follow-up: 46 months). Three-Tesla magnetic resonance imaging brain scans (including brain-substructure volumetrics) were performed annually. Individual-specific rates of change in retinal and brain measures (estimated with linear regression) were correlated, adjusting for age, sex, disease duration, and ...

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    8. Optical coherence tomography reflects brain atrophy in MS: A four year study

      Optical coherence tomography reflects brain atrophy in MS: A four year study

      Objective : To determine whether atrophy of specific retinal layers and brain substructures are associated over time, in order to further validate the utility of optical coherence tomography (OCT) as an indicator of neuronal tissue damage in patients with multiple sclerosis (MS). Methods : Cirrus high definition OCT (including automated macular segmentation) was performed in 107 MS patients biannually (median follow-up: 46-months). Three-tesla magnetic resonance imaging brain scans (including brain-substructure volumetrics) were performed annually. Individual-specific rates of change in retinal and brain measures (estimated with linear regression) were correlated, adjusting for age, sex, disease duration, and optic neuritis (ON) history. Results : Rates ...

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    9. Segmentation of microcystic macular edema in Cirrus OCT scans with an exploratory longitudinal study

      Segmentation of microcystic macular edema in Cirrus OCT scans with an exploratory longitudinal study

      Microcystic macular edema (MME) is a term used to describe pseudocystic spaces in the inner nuclear layer (INL) of the human retina. It has been noted in multiple sclerosis (MS) as well as a variety of other diseases. The processes that lead to MME formation and their change over time have yet to be explained sufficiently. The low rate at which MME occurs within such diverse patient groups makes the identification and consistent quantification of this pathology important for developing patient-specific prognoses. MME is observed in optical coherence tomography (OCT) scans of the retina as changes in light reflectivity in ...

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    10. Longitudinal graph-based segmentation of macular OCT using fundus alignment

      Longitudinal graph-based segmentation of macular OCT using fundus alignment

      Segmentation of retinal layers in optical coherence tomography (OCT) has become an important diagnostic tool for a variety of ocular and neurological diseases. Currently all OCT segmentation algorithms analyze data independently, ignoring previous scans, which can lead to spurious measurements due to algorithm variability and failure to identify subtle changes in retinal layers. In this paper, we present a graph-based segmentation framework to provide consistent longitudinal segmentation results. Regularization over time is accomplished by adding weighted edges between corresponding voxels at each visit. We align the scans to a common subject space before connecting the graphs by registering the data ...

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    11. Automatic segmentation of microcystic macular edema in OCT

      Automatic segmentation of microcystic macular edema in OCT

      Microcystic macular edema (MME) manifests as small, hyporeflective cystic areas within the retina. For reasons that are still largely unknown, a small proportion of patients with multiple sclerosis (MS) develop MME—predominantly in the inner nuclear layer. These cystoid spaces, denoted pseudocysts, can be imaged using optical coherence tomography (OCT) where they appear as small, discrete, low intensity areas with high contrast to the surrounding tissue. The ability to automatically segment these pseudocysts would enable a more detailed study of MME than has been previously possible. Although larger pseudocysts often appear quite clearly in the OCT images, the multi-frame averaging ...

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    12. Analysis of macular OCT images using deformable registration

      Analysis of macular OCT images using deformable registration

      Optical coherence tomography (OCT) of the macula has become increasingly important in the investigation of retinal pathology. However, deformable image registration, which is used for aligning subjects for pairwise comparisons, population averaging, and atlas label transfer, has not been well–developed and demonstrated on OCT images. In this paper, we present a deformable image registration approach designed specifically for macular OCT images. The approach begins with an initial translation to align the fovea of each subject, followed by a linear rescaling to align the top and bottom retinal boundaries. Finally, the layers within the retina are aligned by a deformable ...

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    13. An adaptive grid for graph-based segmentation in retinal OCT

      An adaptive grid for graph-based segmentation in retinal OCT

      Graph-based methods for retinal layer segmentation have proven to be popular due to their efficiency and accuracy. These methods build a graph with nodes at each voxel location and use edges connecting nodes to encode the hard constraints of each layer's thickness and smoothness. In this work, we explore deforming the regular voxel grid to allow adjacent vertices in the graph to more closely follow the natural curvature of the retina. This deformed grid is constructed by fixing node locations based on a regression model of each layer's thickness relative to the overall retina thickness, thus we generate ...

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    14. Multiple-object geometric deformable model for segmentation of macular OCT

      Multiple-object geometric deformable model for segmentation of macular OCT

      Optical coherence tomography (OCT) is the de facto standard imaging modality for ophthalmological assessment of retinal eye disease, and is of increasing importance in the study of neurological disorders. Quantification of the thicknesses of various retinal layers within the macular cube provides unique diagnostic insights for many diseases, but the capability for automatic segmentation and quantification remains quite limited. While manual segmentation has been used for many scientific studies, it is extremely time consuming and is subject to intra- and inter-rater variation. This paper presents a new computational domain, referred to as flat space, and a segmentation method for specific ...

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    15. Retinal layer segmentation of macular OCT images using boundary classification

      Retinal layer segmentation of macular OCT images using boundary classification

      Optical coherence tomography (OCT) has proven to be an essential imaging modality for ophthalmology and is proving to be very important in neurology. OCT enables high resolution imaging of the retina, both at the optic nerve head and the macula. Macular retinal layer thicknesses provide useful diagnostic information and have been shown to correlate well with measures of disease severity in several diseases. Since manual segmentation of these layers is time consuming and prone to bias, automatic segmentation methods are critical for full utilization of this technology. In this work, we build a random forest classifier to segment eight retinal ...

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    16. Segmentation of retinal OCT images using a random forest classifier

      Segmentation of retinal OCT images using a random forest classifier

      Optical coherence tomography (OCT) has become one of the most common tools for diagnosis of retinal abnormalities. Both retinal morphology and layer thickness can provide important information to aid in the differential diagnosis of these abnormalities. Automatic segmentation methods are essential to providing these thickness measurements since the manual delineation of each layer is cumbersome given the sheer amount of data within each OCT scan. In this work, we propose a new method for retinal layer segmentation using a random forest classifier. A total of seven features are extracted from the OCT data and used to simultaneously classify nine layer ...

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    1-16 of 16
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    1. (16 articles) Johns Hopkins University
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    3. (2 articles) The Ohio State University
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    Segmentation of retinal OCT images using a random forest classifier Retinal layer segmentation of macular OCT images using boundary classification Multiple-object geometric deformable model for segmentation of macular OCT An adaptive grid for graph-based segmentation in retinal OCT Analysis of macular OCT images using deformable registration Longitudinal graph-based segmentation of macular OCT using fundus alignment Segmentation of microcystic macular edema in Cirrus OCT scans with an exploratory longitudinal study Optical coherence tomography reflects brain atrophy in MS: A four year study Optical coherence tomography reflects brain atrophy in multiple sclerosis: A four-year study Voxel based morphometry in optical coherence tomography: validation and core findings Real-time and non-invasive measurements of cell mechanical behaviour with optical coherence phase microscopy The Future of Imaging in Detecting Glaucoma Progression