1. Articles from Minhaj Alam

    1-10 of 10
    1. Supervised Machine Learning Based Multi-Task Artificial Intelligence Classification of Retinopathies

      Supervised Machine Learning Based Multi-Task Artificial Intelligence Classification of Retinopathies

      Artificial intelligence (AI) classification holds promise as a novel and affordable screening tool for clinical management of ocular diseases. Rural and underserved areas, which suffer from lack of access to experienced ophthalmologists may particularly benefit from this technology. Quantitative optical coherence tomography angiography (OCTA) imaging provides excellent capability to identify subtle vascular distortions, which are useful for classifying retinovascular diseases. However, application of AI for differentiation and classification of multiple eye diseases is not yet established. In this study, we demonstrate supervised machine learning based multi-task OCTA classification. We sought 1) to differentiate normal from diseased ocular conditions, 2) to ...

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      Mentions: Xincheng Yao
    2. Fully automated geometric feature analysis in optical coherence tomography angiography for objective classification of diabetic retinopathy

      Fully automated geometric feature analysis in optical coherence tomography angiography for objective classification of diabetic retinopathy

      This study is to establish quantitative features of vascular geometry in optical coherence tomography angiography (OCTA) and validate them for the objective classification of diabetic retinopathy (DR). Six geometric features, including total vessel branching angle (VBA: θ), child branching angles (CBAs: α1 and α2), vessel branching coefficient (VBC), and children-to-parent vessel width ratios (VWR1 and VWR2), were automatically derived from each vessel branch in OCTA. Comparative analysis of heathy control, diabetes with no DR (NoDR), and non-proliferative DR (NPDR) was conducted. Our study reveals four quantitative OCTA features to produce robust DR detection and staging classification: (ANOVA, P<0.05), VBA ...

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      Mentions: Xincheng Yao
    3. Supervised machine learning based multi-task artificial intelligence classification of retinopathies

      Supervised machine learning based multi-task artificial intelligence classification of retinopathies

      Artificial intelligence (AI) classification holds promise as a novel and affordable screening tool for clinical management of ocular diseases. Rural and underserved areas, which suffer from lack of access to experienced ophthalmologists may particularly benefit from this technology. Quantitative optical coherence tomography angiography (OCTA) imaging provides excellent capability to identify subtle vascular distortions, which are useful for classifying retinovascular diseases. However, application of AI for differentiation and classification of multiple eye diseases is not yet established. In this study, we demonstrate supervised machine learning based multi-task OCTA classification. We sought 1) to differentiate normal from diseased ocular conditions, 2) to ...

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      Mentions: Xincheng Yao
    4. Near infrared oximetry-guided artery–vein classification in optical coherence tomography angiography

      Near infrared oximetry-guided artery–vein classification in optical coherence tomography angiography

      Differential artery–vein analysis is valuable for early detection of diabetic retinopathy and other eye diseases. As a new optical coherence tomography imaging modality, optical coherence tomography angiography provides capillary level resolution for accurate examination of retinal vasculatures. However, differential artery–vein analysis in optical coherence tomography angiography particularly for macular region in which blood vessels are small is challenging. In coordination with an automatic vessel tracking algorithm, we report here the feasibility of using near infrared optical coherence tomography oximetry to guide artery–vein classification in optical coherence tomography angiography of macular region. Impact statement It is known that ...

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      Mentions: Xincheng Yao
    5. OCT feature analysis guided artery-vein differentiation in OCTA

      OCT feature analysis guided artery-vein differentiation in OCTA

      Differential artery-vein analysis promises better sensitivity for retinal disease detection and classification. However, clinical optical coherence tomography angiography (OCTA) instruments lack the function of artery-vein differentiation. This study aims to verify the feasibility of using OCT intensity feature analysis to guide artery-vein differentiation in OCTA. Four OCT intensity profile features, including i) ratio of vessel width to central reflex, ii) average of maximum profile brightness, iii) average of median profile intensity, and iv) optical density of vessel boundary intensity compared to background intensity, are used to classify artery-vein source nodes in OCT. A blood vessel tracking algorithm is then employed ...

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      Mentions: Xincheng Yao
    6. Comparative Optical Coherence Tomography Angiography of Wild-Type and rd10 Mouse Retinas

      Comparative Optical Coherence Tomography Angiography of Wild-Type and rd10 Mouse Retinas

      Purpose : To conduct longitudinal optical coherence tomography angiography (OCTA) to characterize dynamic changes of trilaminar vascular plexuses in wild-type (WT) and retinal degeneration 10 (rd10) mouse retinas. Methods : Longitudinal in vivo OCT/OCTA measurements of WT and rd10 mouse retinas were conducted at postnatal day 14 (P14), P17, P21, P24, and P28. OCT images were used to quantify retinal thickness changes, while OCTA images were used to investigate vascular dynamics within the trilaminar vascular plexuses, that is, superficial vascular plexus (SVP), intermediate capillary plexus (ICP), and deep capillary plexus (DCP). Blood vessel densities of all three plexus layers were quantitatively ...

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      Mentions: Xincheng Yao
    7. Color Fundus Image Guided Artery-Vein Differentiation in Optical Coherence Tomography Angiography

      Color Fundus Image Guided Artery-Vein Differentiation in Optical Coherence Tomography Angiography

      Purpose : This study aimed to develop a method for automated artery-vein classification in optical coherence tomography angiography (OCTA), and to verify that differential artery-vein analysis can improve the sensitivity of OCTA detection and staging of diabetic retinopathy (DR). Methods : For each patient, the color fundus image was used to guide the artery-vein differentiation in the OCTA image. Traditional mean blood vessel caliber (m-BVC) and mean blood vessel tortuosity (m-BVT) in OCTA images were quantified for control and DR groups. Artery BVC (a-BVC), vein BVC (v-BVC), artery BVT (a-BVT), and vein BVT (a-BVT) were calculated, and then the artery-vein ratio (AVR ...

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      Mentions: Xincheng Yao
    8. Functional optical coherence tomography of neurovascular coupling interactions in the retina

      Functional optical coherence tomography of neurovascular coupling interactions in the retina

      Quantitative evaluation of retinal neurovascular coupling is essential for a better understanding of visual function and early detection of eye diseases. However, there is no established method to monitor coherent interactions between stimulus‐evoked neural activity and hemodynamic responses at high resolution. Here we report a multi‐modal functional optical coherence tomography (OCT) imaging methodology to enable concurrent intrinsic optical signal (IOS) imaging of stimulus‐evoked neural activity and hemodynamic responses at capillary resolution. OCT angiography guided IOS analysis was used to separate neural‐IOS and hemodynamic‐IOS changes in the same retinal image sequence. Frequency flicker stimuli evoked neural ...

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      Mentions: Xincheng Yao
    9. Computer-aided classification of sickle cell retinopathy using quantitative features in optical coherence tomography angiography

      Computer-aided classification of sickle cell retinopathy using quantitative features in optical coherence tomography angiography

      As a new optical coherence tomography (OCT) imaging modality, there is no standardized quantitative interpretation of OCT angiography (OCTA) characteristics of sickle cell retinopathy (SCR). This study is to demonstrate computer-aided SCR classification using quantitative OCTA features, i.e., blood vessel tortuosity (BVT), blood vessel diameter (BVD), vessel perimeter index (VPI), foveal avascular zone (FAZ) area, FAZ contour irregularity, parafoveal avascular density (PAD). It was observed that combined features show improved classification performance, compared to single feature. Three classifiers, including support vector machine (SVM), k-nearest neighbor (KNN) algorithm, and discriminant analysis, were evaluated. Sensitivity, specificity, and accuracy were quantified to ...

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    10. Quantitative characteristics of sickle cell retinopathy in optical coherence tomography angiography

      Quantitative characteristics of sickle cell retinopathy in optical coherence tomography angiography

      Early detection is an essential step for effective intervention of sickle cell retinopathy (SCR). Emerging optical coherence tomography angiography (OCTA) provides excellent three-dimensional (3D) resolution to enable label-free, noninvasive visualization of retinal vascular structures, promising improved sensitivity in detecting SCR. However, quantitative analysis of SCR characteristics in OCTA images is yet to be established. In this study, we conducted comprehensive analysis of six OCTA parameters, including blood vessel tortuosity, vessel diameter, vessel perimeter index (VPI), area of foveal avascular zone (FAZ), contour irregularity of FAZ and parafoveal avascular density. Compared to traditional retinal thickness analysis, five of these six OCTA ...

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      Mentions: Xincheng Yao
    1-10 of 10
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    1. (10 articles) Xincheng Yao
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    Quantitative characteristics of sickle cell retinopathy in optical coherence tomography angiography Computer-aided classification of sickle cell retinopathy using quantitative features in optical coherence tomography angiography Functional optical coherence tomography of neurovascular coupling interactions in the retina Color Fundus Image Guided Artery-Vein Differentiation in Optical Coherence Tomography Angiography Comparative Optical Coherence Tomography Angiography of Wild-Type and rd10 Mouse Retinas OCT feature analysis guided artery-vein differentiation in OCTA Near infrared oximetry-guided artery–vein classification in optical coherence tomography angiography Supervised machine learning based multi-task artificial intelligence classification of retinopathies Fully automated geometric feature analysis in optical coherence tomography angiography for objective classification of diabetic retinopathy Supervised Machine Learning Based Multi-Task Artificial Intelligence Classification of Retinopathies Image contrast correction method in full-field optical coherence tomography Evaluation of posterior vitreous detachment using ultrasonography and optical coherence tomography