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506 full-text articles. Page 1 of 19.

Morphological Assessment Of The Retina In Uveitis., Michael M. Altaweel, Sapna S. Gangaputra, Jennifer E. Thorne, James P. Dunn, Susan G. Elner, Glenn J. Jaffe, Rosa Y. Kim, P. Kumar Rao, Susan B. Reed, John H. Kempen 2016 University of Wisconsin-Madison

Morphological Assessment Of The Retina In Uveitis., Michael M. Altaweel, Sapna S. Gangaputra, Jennifer E. Thorne, James P. Dunn, Susan G. Elner, Glenn J. Jaffe, Rosa Y. Kim, P. Kumar Rao, Susan B. Reed, John H. Kempen

Wills Eye Institute Papers

BACKGROUND: The objective of this study is to describe a system for color photograph evaluation in uveitis and report baseline morphologic findings for the Multicenter Uveitis Steroid Treatment (MUST) Trial. Four-hundred seventy-nine eyes of 255 subjects with intermediate, posterior, and panuveitis had stereoscopic color fundus photographs obtained by certified photographers and evaluated by certified graders using standardized procedures to evaluate morphologic characteristics of uveitis. The posterior pole was evaluated for macular edema, vitreoretinal interface abnormalities, and macular pigment disturbance/atrophy; the optic disk was assessed for edema, pallor, or glaucomatous changes. The presence of neovascularization, vascular occlusion, vascular sheathing, and ...


Self-Complementary Adeno-Associated Virus Vectors Improve Transduction Efficiency Of Corneal Endothelial Cells, Anja K. Gruenert, Marta Czugala, Christian Mueller, Marco Schmeer, Martin Schleef, Friedrich E. Kruse, Thomas A. Fuchsluger 2016 University of Erlangen-Nurnberg

Self-Complementary Adeno-Associated Virus Vectors Improve Transduction Efficiency Of Corneal Endothelial Cells, Anja K. Gruenert, Marta Czugala, Christian Mueller, Marco Schmeer, Martin Schleef, Friedrich E. Kruse, Thomas A. Fuchsluger

Christian Mueller

Transplantation of a donor cornea to restore vision is the most frequently performed transplantation in the world. Corneal endothelial cells (CEC) are crucial for the outcome of a graft as they maintain corneal transparency and avoid graft failure due to corneal opaqueness. Given the characteristic of being a monolayer and in direct contact with culture medium during cultivation in eye banks, CEC are specifically suitable for gene therapeutic approaches prior to transplantation. Recombinant adeno-associated virus 2 (rAAV2) vectors represent a promising tool for gene therapy of CEC. However, high vector titers are needed to achieve sufficient gene expression. One of ...


Vessel Extraction For As-Oct Angiography, Huazhu Fu, Yanwu Xu, Damon Wing Kee Wong, Marcus Ang, Suchandrima Das, Jiang Liu 2016 University of Iowa

Vessel Extraction For As-Oct Angiography, Huazhu Fu, Yanwu Xu, Damon Wing Kee Wong, Marcus Ang, Suchandrima Das, Jiang Liu

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

In this work, we propose a filter-based vessel segmentation method for Anterior Segment Optical Coherence Tomography Angiography image. In our method, the bandpass filter is utilized to suppress the horizontal noise lines caused by eye movement, while the curvedsupport Gaussian filter is utilized to enhance the vessel and generate the probability map.


Diabetic Macular Edema Grading Based On Deep Neural Networks, Baidaa Al-Bander, Waleed Al-Nuaimy, Majid A. Al-Taee, Bryan M. Williams, Yalin Zheng 2016 University of Iowa

Diabetic Macular Edema Grading Based On Deep Neural Networks, Baidaa Al-Bander, Waleed Al-Nuaimy, Majid A. Al-Taee, Bryan M. Williams, Yalin Zheng

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Diabetic Macular Edema (DME) is a major cause of vision loss in diabetes. Its early detection and treatment is therefore a vital task in management of diabetic retinopathy. In this paper, we propose a new featurelearning approach for grading the severity of DME using color retinal fundus images. An automated DME diagnosis system based on the proposed featurelearning approach is developed to help early diagnosis of the disease and thus averts (or delays) its progression. It utilizes the convolutional neural networks (CNNs) to identify and extract features of DME automatically without any kind of user intervention. The developed prototype was ...


Automatic Optic Disc Abnormality Detection In Fundus Images: A Deep Learning Approach, Hanan S. Alghamdi, Hongying Lilian Tang, Saad A. Waheeb, Tunde Peto 2016 University of Iowa

Automatic Optic Disc Abnormality Detection In Fundus Images: A Deep Learning Approach, Hanan S. Alghamdi, Hongying Lilian Tang, Saad A. Waheeb, Tunde Peto

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Optic disc (OD) is a key structure in retinal images. It serves as an indicator to detect various diseases such as glaucoma and changes related to new vessel formation on the OD in diabetic retinopathy (DR) or retinal vein occlusion. OD is also essential to locate structures such as the macula and the main vascular arcade. Most existing methods for OD localization are rule-based, either exploiting the OD appearance properties or the spatial relationship between the OD and the main vascular arcade. The detection of OD abnormalities has been performed through the detection of lesions such as hemorrhaeges or through ...


Retinal Image Quality Classification Using Neurobiological Models Of The Human Visual System, Dwarikanath Mahapatra 2016 University of Iowa

Retinal Image Quality Classification Using Neurobiological Models Of The Human Visual System, Dwarikanath Mahapatra

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Retinal image quality assessment (IQA) algorithms use different hand crafted features without considering the important role of the human visual system (HVS). We solve the IQA problem using the principles behind the working of the HVS. Unsupervised information from local saliency maps and supervised information from trained convolutional neural networks (CNNs) are combined to make a final decision on image quality. A novel algorithm is proposed that calculates saliency values for every image pixel at multiple scales to capture global and local image information. This extracts generalized image information in an unsupervised manner while CNNs provide a principled approach to ...


Automated Tessellated Fundus Detection In Color Fundus Images, Mengdi Xu, Jun Cheng, Damon Wing Kee Wong, Ching-Yu Cheng, Seang Mei Saw, Tien Yin Wong 2016 University of Iowa

Automated Tessellated Fundus Detection In Color Fundus Images, Mengdi Xu, Jun Cheng, Damon Wing Kee Wong, Ching-Yu Cheng, Seang Mei Saw, Tien Yin Wong

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

In this work, we propose an automated tessellated fundus detection method by utilizing texture features and color features. Color moments, Local Binary Patterns (LBP), and Histograms of Oriented Gradients (HOG) are extracted to represent the color fundus image. After feature extraction, a SVM classifier is trained to detect the tessellated fundus. Both linear and RBF kernels are applied and compared in this work. A dataset with 836 fundus images is built to evaluate the proposed method. For linear SVM, the mean accuracy of 98% is achieved, with sensitivity of 0.99 and specificity of 0.98. For RBF kernel, the ...


Anterior Chamber Angle Assessment System, Huazhu Fu, Yanwu Xu, Damon Wing Kee Wong, Jiang Liu, Mani Baskaran, Shamira A. Perera, Tin Aung 2016 University of Iowa

Anterior Chamber Angle Assessment System, Huazhu Fu, Yanwu Xu, Damon Wing Kee Wong, Jiang Liu, Mani Baskaran, Shamira A. Perera, Tin Aung

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

In this paper, we propose an automatic anterior chamber angle assessment system for Anterior Segment Optical Coherence Tomography (AS-OCT). In our system, the automatic segmentation method is used to segment the clinical structures, which are then used to recover standard clinical ACA measurements. Our measurements can not only support clinical assessments, but also be utilized as features for detecting anterior angle closure in automatic glaucoma diagnosis.


Motion Correction In Optical Coherence Tomography For Multi-Modality Retinal Image Registration, Jun Cheng, Jimmy Addison Lee, Guozhen Xu, Ying Quan, Ee Ping Ong, Damon Wing Kee Wong 2016 University of Iowa

Motion Correction In Optical Coherence Tomography For Multi-Modality Retinal Image Registration, Jun Cheng, Jimmy Addison Lee, Guozhen Xu, Ying Quan, Ee Ping Ong, Damon Wing Kee Wong

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Optical coherence tomography (OCT) is a recently developed non-invasive imaging modality, which is often used in ophthalmology. Because of the sequential scanning in form of A-scans, OCT suffers from the inevitable eye movement. This often leads to mis-alignment especially among consecutive B-scans, which affects the analysis and processing of the data such as the registration of the OCT en face image to color fundus image. In this paper, we propose a novel method to correct the mis-alignment among consecutive B-scans to improve the accuracy in multi-modality retinal image registration. In the method, we propose to compute decorrelation from overlapping B-scans ...


Geometric Connectivity Analysis Based On Edge Co-Occurrences In Retinal Images, Samaneh Abbasi-Sureshjani, Jiong Zhang, Gonzalo Sanguinetti, Remco Duits, Bart ter Haar Romeny 2016 University of Iowa

Geometric Connectivity Analysis Based On Edge Co-Occurrences In Retinal Images, Samaneh Abbasi-Sureshjani, Jiong Zhang, Gonzalo Sanguinetti, Remco Duits, Bart Ter Haar Romeny

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

No abstract provided.


Artefacts Removal From Optical Coherence Tomography Angiography, Ee Ping Ong, Jun Cheng, Ying Quan, Guozhen Xu, Damon W.K. Wong 2016 University of Iowa

Artefacts Removal From Optical Coherence Tomography Angiography, Ee Ping Ong, Jun Cheng, Ying Quan, Guozhen Xu, Damon W.K. Wong

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

This paper presents a new approach for artefacts removal from optical coherence tomography angiography (OCTA). The artefacts mainly arise as a result of distortion due to eye movements during OCT scanning process. These distortions manifest themselves as visible motion artefacts when doctors review the enface image of OCTA data. To remove these artefacts, firstly we perform motion registration for the captured OCT volume data and subsequently perform motion correction to obtain the registered OCT data. Next, we compute the OCTA from the registered OCT data using an enhanced correlation mapping technique. Thereafter, we compute the enface image from the OCTA ...


Optic Cup Segmentation Using Large Pixel Patch Based Cnns, Yundi Guo, Beiji Zou, Zailiang Chen, Qi He, Qing Liu, Rongchang Zhao 2016 University of Iowa

Optic Cup Segmentation Using Large Pixel Patch Based Cnns, Yundi Guo, Beiji Zou, Zailiang Chen, Qi He, Qing Liu, Rongchang Zhao

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Optic cup(OC) segmentation on color fundus image is essential for the calculation of cup-to-disk ratio and fundus morphological analysis, which are very important references in the diagnosis of glaucoma. In this paper we proposed an OC segmentation method using convolutional neural networks(CNNs) to learn from big size patch belong to each pixel. The segmentation result is achieved by classification of each pixel patch and postprocessing. With large pixel patch, the network could learn more global information around each pixel and make a better judgement during classification. We tested this method on public dataset Drishti-GS and achieved average F-Score ...


Infrastructure For Retinal Image Analysis, Behdad Dashtbozorg, Samaneh Abbasi-Sureshjani, Jiong Zhang, Fan Huang, Erik Bekkers, Bart ter Haar Romeny 2016 University of Iowa

Infrastructure For Retinal Image Analysis, Behdad Dashtbozorg, Samaneh Abbasi-Sureshjani, Jiong Zhang, Fan Huang, Erik Bekkers, Bart Ter Haar Romeny

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

This paper introduces a retinal image analysis infrastructure for the automatic assessment of biomarkers related to early signs of diabetes, hypertension and other systemic diseases. The developed application provides several tools, namely normalization, vessel enhancement and segmentation, optic disc and fovea detection, junction detection, bifurcation/crossing discrimination, artery/vein classification and red lesion detection. The pipeline of these methods allows the assessment of important biomarkers characterizing dynamic properties of retinal vessels, such as tortuosity, width, fractal dimension and bifurcation geometry features.


Bridging Disconnected Curvilinear Structures Via Numerical Evolutions Of Completion Process In Ophthalmologic Images, Jiong Zhang, Erik Bekkers, Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart ter Haar Romeny 2016 University of Iowa

Bridging Disconnected Curvilinear Structures Via Numerical Evolutions Of Completion Process In Ophthalmologic Images, Jiong Zhang, Erik Bekkers, Samaneh Abbasi-Sureshjani, Behdad Dashtbozorg, Bart Ter Haar Romeny

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

No abstract provided.


Evaluation Of The Areas Involved In Visual Cortex In Parkinson's Disease Using Diffusion Tensor Imaging, Somayeh Mohammadi Jooyandeh, Aida Kamalian, Sepideh Shiranvand, Mahsa Dolatshahi, Mohammad Hadi Shadmehr, Thomas C. Baghai, Farzaneh Rahmani, Ahmad Shojaie, Mohammad H. Aarabi 2016 University of Iowa

Evaluation Of The Areas Involved In Visual Cortex In Parkinson's Disease Using Diffusion Tensor Imaging, Somayeh Mohammadi Jooyandeh, Aida Kamalian, Sepideh Shiranvand, Mahsa Dolatshahi, Mohammad Hadi Shadmehr, Thomas C. Baghai, Farzaneh Rahmani, Ahmad Shojaie, Mohammad H. Aarabi

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Parkinson's disease (PD) is a progressive neurodegenerative disorder assumed to involve different areas of CNS and PNS. In PD patients and in primates with experimental Parkinsonism indicating that retinal dopamine deficiency is an important factor in the pathogenesis of PD visual dysfunction. Visual signs and symptoms of PD may include defects in eye movement, pupillary function, and in more complex visual tasks. In this study, we evaluated the areas involved in visual cortex in PD by diffusion tensor imaging to assess the structural change in PD.


Predicting Drusen Regression From Oct In Patients With Age-Related Macular Degeneration, Hrvoje Bogunović, Alessio Montuoro, Sebastian M. Waldstein, Magdalena Baratsits, Ferdinand Schlanitz, Ursula Schmidt-Erfurth 2016 University of Iowa

Predicting Drusen Regression From Oct In Patients With Age-Related Macular Degeneration, Hrvoje Bogunović, Alessio Montuoro, Sebastian M. Waldstein, Magdalena Baratsits, Ferdinand Schlanitz, Ursula Schmidt-Erfurth

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Age-related macular degeneration (AMD) is a leading cause of blindness in developed countries. The presence of drusen is the hallmark of early/intermediate AMD, and their sudden regression is strongly associated with the onset of late AMD. In this work we propose a predictive model of drusen regression using optical coherence tomography (OCT) based features. First, a series of automated image analysis steps are applied to segment and characterize individual drusen and their development. Second, from a set of quantitative features, a random forest classifiser is employed to predict the occurrence of individual drusen regression within the following 12 months ...


A Novel Machine Learning Model Based On Exudate Localization To Detect Diabetic Macular Edema, Oscar Perdomo, Sebastian Otalora, Francisco Rodríguez, John Arevalo, Fabio A. González 2016 University of Iowa

A Novel Machine Learning Model Based On Exudate Localization To Detect Diabetic Macular Edema, Oscar Perdomo, Sebastian Otalora, Francisco Rodríguez, John Arevalo, Fabio A. González

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

Diabetic macular edema is one of the leading causes of legal blindness worldwide. Early, and accessible, detection of ophthalmological diseases is especially important in developing countries, where there are major limitations to access to specialized medical diagnosis and treatment. Deep learning models, such as deep convolutional neural networks have shown great success in different computer vision tasks. In medical images they have been also applied with great success. The present paper presents a novel strategy based on convolutional neural networks to combine exudates localization and eye fundus images for automatic classification of diabetic macular edema as a support for diabetic ...


Retinal Vessel Segmentation From Simple To Difficult, Qing Liu, Beiji Zou, Jie Chen, Zailiang Chen, Chengzhang Zhu, Kejuan Yue, Guoying Zhao 2016 University of Iowa

Retinal Vessel Segmentation From Simple To Difficult, Qing Liu, Beiji Zou, Jie Chen, Zailiang Chen, Chengzhang Zhu, Kejuan Yue, Guoying Zhao

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

In this paper, we propose two vesselness maps and a simple to difficult learning framework for retinal vessel segmentation which is ground truth free. The first vesselness map is the multiscale centrelineboundary contrast map which is inspired by the appearance of vessels. The other is the difference of diffusion map which measures the difference of the diffused image and the original one. Meanwhile, two existing vesselness maps are generated. Totally, 4 vesselness maps are generated. In each vesselness map, pixels with large vesselness values are regarded as positive samples. Pixels around the positive samples with small vesselness values are regarded ...


Image Quality Classification For Dr Screening Using Convolutional Neural Networks, Ruwan Tennakoon, Dwarikanath Mahapatra, Pallab Roy, Suman Sedai, Rahil Garnavi 2016 University of Iowa

Image Quality Classification For Dr Screening Using Convolutional Neural Networks, Ruwan Tennakoon, Dwarikanath Mahapatra, Pallab Roy, Suman Sedai, Rahil Garnavi

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

The quality of input images significantly affects the outcome of automated diabetic retinopathy screening systems. Current methods to identify image quality rely on hand-crafted geometric and structural features, that does not generalize well. We propose a new method for retinal image quality classification (IQC) that uses computational algorithms imitating the working of the human visual systems. The proposed method leverages on learned supervised information using convolutional neural networks (CNN), thus avoiding hand-engineered features. Our analysis shows that the learned features capture both geometric and structural information relevant for image quality classification. Experimental results conducted on a relatively large dataset demonstrates ...


Stereo Eye Tracking With A Single Camera For Ocular Tumor Therapy, Stephan Wyder, Philippe C. Cattin 2016 University of Iowa

Stereo Eye Tracking With A Single Camera For Ocular Tumor Therapy, Stephan Wyder, Philippe C. Cattin

Proceedings of the Ophthalmic Medical Image Analysis International Workshop

We present a compact and accurate stereo eye tracking system using only one physical camera. The proposed eye tracking system is intended as a navigation system for ocular tumor therapy. There, the available physical space to mount an eye tracker is limited. Furthermore, high system accuracy is demanded. However, high eye tracker accuracy and system compactness often disagree. Current established eye trackers can live with that compromise, desktop devices focus more on accuracy whereas mobile devices focus on compactness. We combine a stereo eye tracking algorithm with a clever arrangement of two planar mirrors and a single camera to get ...


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