1. Articles from Michaël J. A. Girard

    1-24 of 36 1 2 »
    1. OCT-GAN: single step shadow and noise removal from optical coherence tomography images of the human optic nerve head

      OCT-GAN: single step shadow and noise removal from optical coherence tomography images of the human optic nerve head

      Speckle noise and retinal shadows within OCT B-scans occlude important edges, fine textures and deep tissues, preventing accurate and robust diagnosis by algorithms and clinicians. We developed a single process that successfully removed both noise and retinal shadows from unseen single-frame B-scans within 10.4ms. Mean average gradient magnitude (AGM) for the proposed algorithm was 57.2% higher than current state-of-the-art, while mean peak signal to noise ratio (PSNR), contrast to noise ratio (CNR), and structural similarity index metric (SSIM) increased by 11.1%, 154% and 187% respectively compared to single-frame B-scans. Mean intralayer contrast (ILC) improvement for the retinal ...

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    2. Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images

      Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images

      Background/Aims Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosis and treatment of many eye diseases, especially angle-closure glaucoma. Method In this study, we developed a deep convolutional neural network (DCNN) for the localisation of the scleral spur; moreover, we introduced an information-rich segmentation approach for this localisation problem. An ensemble of DCNNs for the segmentation of AS structures (iris, corneosclera shell adn anterior chamber) was developed. Based on the results of two previous processes, an algorithm to automatically quantify clinically important ...

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    3. Longitudinal assessment of optic nerve head changes using optical coherence tomography in a primate microbead model of ocular hypertension

      Longitudinal assessment of optic nerve head changes using optical coherence tomography in a primate microbead model of ocular hypertension

      In humans, the longitudinal characterisation of early optic nerve head (ONH) damage in ocular hypertension (OHT) is difficult as patients with glaucoma usually have structural ONH damage at the time of diagnosis. Previous studies assessed glaucomatous ONH cupping by measuring the anterior lamina cribrosa depth (LCD) and minimal rim width (MRW) using optical coherence tomography (OCT). In this study, we induced OHT by repeated intracameral microbead injections in 16 cynomolgus primates (10 unilateral; 6 bilateral) and assessed the structural changes of the ONH longitudinally to observe early changes. Elevated intraocular pressure (IOP) in OHT eyes was maintained for 7 months ...

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    4. OCT Optic Nerve Head Morphology in Myopia I: Implications of Anterior Scleral Canal Opening versus Bruch’s Membrane Opening Offset

      OCT Optic Nerve Head Morphology in Myopia I: Implications of Anterior Scleral Canal Opening versus Bruch’s Membrane Opening Offset

      Purpose To measure the magnitude and direction of anterior scleral canal opening (ASCO) offset relative to Bruch’s membrane opening (BMO) (ASCO/BMO offset) in order to characterize neural canal obliqueness and minimum cross-sectional area (NCMCA) in 69 highly myopic and 138 healthy, age-matched, control eyes. Design: Cross-sectional study. Methods Using Optic Coherence Tomography (OCT) scans of the optic nerve head (ONH), BMO and ASCO were manually segmented and their centroids, size and shape were calculated. ASCO/BMO offset magnitude and direction were measured after projecting the ASCO/BMO centroid vector onto the BMO plane. Neural canal axis obliqueness was ...

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    5. Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning

      Towards Label-Free 3D Segmentation of Optical Coherence Tomography Images of the Optic Nerve Head Using Deep Learning

      Since the introduction of optical coherence tomography (OCT), it has been possible to study the complex 3D morphological changes of the optic nerve head (ONH) tissues that occur along with the progression of glaucoma. Although several deep learning (DL) techniques have been recently proposed for the automated extraction (segmentation) and quantification of these morphological changes, the device-specific nature and the difficulty in preparing manual segmentations (training data) limit their clinical adoption. With several new manufacturers and next-generation OCT devices entering the market, the complexity in deploying DL algorithms clinically is only increasing. To address this, we propose a DLbased 3D ...

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    6. Efficacy and Reproducibility of Attenuation-Compensated Optical Coherence Tomography for Assessing External Elastic Membrane Border and Plaque Composition in Native and Stented Segments ― An In Vivo and Histology-Based Study ―

      Efficacy and Reproducibility of Attenuation-Compensated Optical Coherence Tomography for Assessing External Elastic Membrane Border and Plaque Composition in Native and Stented Segments ― An In Vivo and Histology-Based Study ―

      Background: Attenuation-compensated (AC) technique was recently introduced to improve the plaque characterization of optical coherence tomography (OCT). Histological validation demonstrated promising results but the efficacy and reproducibility of this technique for assessing in-vivo tissue composition remains unclear. Methods and Results: OCT images portraying native (n=200) and stented (n=200) segments and 31 histological cross-sections were analyzed. AC-OCT appeared superior to conventional (C)-OCT in detecting the external elastic lamina (EEM) borders (76% vs. 65.5%); AC-OCT enabled larger EEM arc detection compared with C-OCT (174.2±58.7° vs. 137.5±57.9°; P<0.001). There was poor ...

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    7. DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images

      DeshadowGAN: A Deep Learning Approach to Remove Shadows from Optical Coherence Tomography Images

      Purpose: To remove retinal shadows from optical coherence tomography (OCT) images of the optic nerve head (ONH). Methods: 2328 OCT images acquired through the center of the ONH using a Spectralis OCT machine for both eyes of 13 subjects were used to train a generative adversarial network (GAN) using a custom loss function.Image quality was assessed qualitatively (for artifacts) and quantitatively using the intralayer contrast € a measure of shadow visibility ranging from 0 (shadow-free) to 1 (strong shadow) and compared to compensated images. Œis was computed in the Retinal Nerve Fiber Layer (RNFL), the Inner Plexiform Layer (IPL), the ...

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    8. A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

      A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

      Optical coherence tomography (OCT) has become an established clinical routine for the in vivo imaging of the optic nerve head (ONH) tissues, that is crucial in the diagnosis and management of various ocular and neuro-ocular pathologies. However, the presence of speckle noise affects the quality of OCT images and its interpretation. Although recent frame-averaging techniques have shown to enhance OCT image quality, they require longer scanning durations, resulting in patient discomfort. Using a custom deep learning network trained with 2,328 ‘clean B-scans’ (multi-frame B-scans; signal averaged), and their corresponding ‘noisy B-scans’ (clean B-scans + Gaussian noise), we were able to ...

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    9. Deep Learning Algorithms to Isolate and Quantify the Structures of the Anterior Segment in Optical Coherence Tomography Images

      Deep Learning Algorithms to Isolate and Quantify the Structures of the Anterior Segment in Optical Coherence Tomography Images

      Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosis and treatment of many eye diseases, especially angle closure glaucoma. In this study, we developed a deep convolutional neural network (DCNN) for the localization of the scleral spur, and the segmentation of anterior segment structures (iris, corneo-sclera shell, anterior chamber). With limited training data, the DCNN was able to detect the scleral spur on unseen ASOCT images as accurately as an experienced ophthalmologist; and simultaneously isolated the anterior segment structures with a Dice coefficient ...

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    10. A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

      A Deep Learning Approach to Denoise Optical Coherence Tomography Images of the Optic Nerve Head

      Purpose: To develop a deep learning approach to de-noise optical coherence tomography (OCT) B-scans of the optic nerve head (ONH). Methods: Volume scans consisting of 97 horizontal B-scans were acquired through the center of the ONH using a commercial OCT device (Spectralis) for both eyes of 20 subjects. For each eye, single-frame (without signal averaging), and multi-frame (75x signal averaging) volume scans were obtained. A custom deep learning network was then designed and trained with 2,328 "clean B-scans" (multi-frame B-scans), and their corresponding "noisy B-scans" (clean B-scans + gaussian noise) to de-noise the single-frame B-scans. The performance of the de-noising ...

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    11. DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images

      DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images

      Given that the neural and connective tissues of the optic nerve head (ONH) exhibit complex morphological changes with the development and progression of glaucoma, their simultaneous isolation from optical coherence tomography (OCT) images may be of great interest for the clinical diagnosis and management of this pathology. A deep learning algorithm (custom U-NET) was designed and trained to segment 6 ONH tissue layers by capturing both the local (tissue texture) and contextual information (spatial arrangement of tissues). The overall Dice coefficient (mean of all tissues) was 0.91 ± 0.05 when assessed against manual segmentations performed by an expert observer ...

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    12. DRUNET: A Dilated-Residual U-Net Deep Learning Network to Digitally Stain Optic Nerve Head Tissues in Optical Coherence Tomography Images

      DRUNET: A Dilated-Residual U-Net Deep Learning Network to Digitally Stain Optic Nerve Head Tissues in Optical Coherence Tomography Images

      Given that the neural and connective tissues of the optic nerve head (ONH) exhibit complex morphological changes with the development and progression of glaucoma, their simultaneous isolation from optical coherence tomography (OCT) images may be of great interest for the clinical diagnosis and management of this pathology. A deep learning algorithm was designed and trained to digitally stain (i.e. highlight) 6 ONH tissue layers by capturing both the local (tissue texture) and contextual information (spatial arrangement of tissues). The overall dice coefficient (mean of all tissues) was 0.91 ± 0.05 when assessed against manual segmentations performed by an ...

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    13. Imaging of the lamina cribrosa and its role in glaucoma: a review

      Imaging of the lamina cribrosa and its role in glaucoma: a review

      The lamina cribrosa of the optic nerve head serves two contrasting roles; it must be porous to allow retinal ganglion cell axons to pass through, and yet at the same time, it must also provide adequate structural support to withstand the stresses and strains across it. Improvements in imaging such as optical coherence tomography image capture and image processing have allowed detailed in vivo studies of lamina cribrosa macro- and micro-architectural characteristics. This has aided our understanding of the optic nerve head as a complex biomechanical structure. In this review, we first aim to frame the biomechanical considerations of lamina ...

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    14. A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head

      A Deep Learning Approach to Digitally Stain Optical Coherence Tomography Images of the Optic Nerve Head

      Purpose. To develop a deep learning approach to digitally-stain optical coherence tomography (OCT) images of the optic nerve head (ONH). Methods. A horizontal B-scan was acquired through the center of the ONH using OCT (Spectralis) for 1 eye of each of 100 subjects (40 normal & 60 glaucoma). All images were enhanced using adaptive compensation. A custom deep learning network was then designed and trained with the compensated images to digitally stain (i.e. highlight) 6 tissue layers of the ONH. The accuracy of our algorithm was assessed (against manual segmentations) using the Dice coefficient, sensitivity, and specificity. We further studied ...

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    15. Dynamic Change in Optic Nerve After Intracranial Pressure Reduction in Children

      Dynamic Change in Optic Nerve After Intracranial Pressure Reduction in Children

      Advances in optical coherence tomography (OCT) have enabled researchers to obtain in vivo information regarding the lamina cribrosa (LC) in a noninvasive manner. We used swept-source OCT (SS-OCT) to investigate the dynamic changes in deep anterior optic nerve head (ONH) structures after surgical decompression for increased intracranial pressure (IICP) in pediatric patients.

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    16. Feature Of The Week 05/28/2017: In Vivo 3-Dimensional Strain Mapping Confirms Large Optic Nerve Head Deformations Following Horizontal Eye Movements

      Feature Of The Week 05/28/2017: In Vivo 3-Dimensional Strain Mapping Confirms Large Optic Nerve Head Deformations Following Horizontal Eye Movements

      Glaucoma is characterized by an irreversible damage of retinal ganglion cells within the optic nerve head (ONH) at the back of the eye. Currently we know that elevated intraocular pressure (IOP) is associated with increased prevalence of glaucoma but not all glaucoma patients have an elevated IOP. The biomechanical theory of glaucoma hypothesizes that elevated (or fluctuating) IOP deforms the ONH tissues, including the lamina cribrosa (LC), and that these deformations drive retinal ganglion cell injury and death. However, IOP is not the only load that can deform the ONH. Eye movements have recently been hypothesized to be able to ...

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    17. A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head

      A Digital Staining Algorithm for Optical Coherence Tomography Images of the Optic Nerve Head

      Purpose : To digitally stain spectral-domain optical coherence tomography (OCT) images of the optic nerve head (ONH), and highlight either connective or neural tissues. Methods : OCT volumes of the ONH were acquired from one eye of 10 healthy subjects. We processed all volumes with adaptive compensation to remove shadows and enhance deep tissue visibility. For each ONH, we identified the four most dissimilar pixel-intensity histograms, each of which was assumed to represent a tissue group. These four histograms formed a vector basis on which we ‘projected' each OCT volume in order to generate four digitally stained volumes P1 to P4. Digital ...

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    18. In Vivo 3-Dimensional Strain Mapping Confirms Large Optic Nerve Head Deformations Following Horizontal Eye Movements

      In Vivo 3-Dimensional Strain Mapping Confirms Large Optic Nerve Head Deformations Following Horizontal Eye Movements

      Purpose : To measure lamina cribrosa (LC) strains (deformations) following abduction and adduction in healthy subjects and to compare them with those resulting from a relatively high acute intraocular pressure (IOP) elevation. Methods : A total of 16 eyes from 8 healthy subjects were included. Among the 16 eyes, 11 had peripapillary atrophy (PPA). For each subject, both optic nerve heads (ONHs) were imaged using optical coherence tomography (OCT) at baseline (twice), in different gaze positions (adduction and abduction of 20°) and following an acute IOP elevation of approximately 20 mm Hg from baseline (via ophthalmodynamometry). Strains of LC for all loading ...

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    19. Positional and Curvature Difference of Lamina Cribrosa According to the Baseline Intraocular Pressure in Primary Open-Angle Glaucoma: A Swept-Source Optical Coherence Tomography (SS-OCT) Study

      Positional and Curvature Difference of Lamina Cribrosa According to the Baseline Intraocular Pressure in Primary Open-Angle Glaucoma: A Swept-Source Optical Coherence Tomography (SS-OCT) Study

      Purpose To investigate the variation of lamina cribrosa (LC) structure based on the baseline intraocular pressure (IOP) in eyes with primary open-angle glaucoma (POAG) and healthy individuals using swept-source optical coherence tomography. Methods A total of 108 eyes with POAG and 61 healthy eyes were recruited. Based on the baseline IOP, the POAG eyes were divided into higher-baseline IOP (HTG; baseline IOP > 21 mmHg, n = 38 eyes) and lower-baseline IOP (NTG; baseline IOP ≤ 21 mmHg, n = 70 eyes). The anterior laminar insertion depth (ALID), mean LC depth (mLCD), and the LC curvature index (mLCD–ALID) were measured, and compared among ...

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    20. Enhancement of Corneal Visibility in Optical Coherence Tomography Images with Corneal Opacification

      Enhancement of Corneal Visibility in Optical Coherence Tomography Images with Corneal Opacification

      Purpose : To establish and to rank the performance of a corneal adaptive compensation (CAC) algorithm in enhancing corneal images with scars acquired from three commercially available anterior segment optical coherence tomography (ASOCT) devices. Methods : Horizontal B-scans of the cornea were acquired from 10 patients using three ASOCT devices (Spectralis, RTVue, and Cirrus). We compared ASOCT image quality (with and without CAC) by computing the intralayer contrast (a measure of shadow removal), the interlayer contrast (a measure of tissue boundary visibility), and the tissue/background contrast (a measure of overall corneal visibility). All six groups (Spectralis, RTVue, Cirrus, Spectralis+CAC, RTVue ...

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    21. Optimization of coronary optical coherence tomography imaging using the attenuation-compensated technique: a validation study

      Optimization of coronary optical coherence tomography imaging using the attenuation-compensated technique: a validation study

      Purpose To optimize conventional coronary optical coherence tomography (OCT) images using the attenuation-compensated technique to improve identification of plaques and the external elastic lamina (EEL) contour. Method The attenuation-compensated technique was optimized via manipulating contrast exponent C, and compression exponent N, to achieve an optimal contrast and signal-to-noise ratio (SNR). This was applied to 60 human coronary lesions (38 native and 22 stented) ex vivo conventional coronary OCT images acquired from heart autopsies of 10 patients and matching histology was available as reference. Three independent reviewers assessed the conventional and attenuation-compensated OCT images blindly for plaque characteristics and EEL detection ...

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    22. In Vivo 3-Dimensional Strain Mapping of the Optic Nerve Head Following Intraocular Pressure Lowering by Trabeculectomy

      In Vivo 3-Dimensional Strain Mapping of the Optic Nerve Head Following Intraocular Pressure Lowering by Trabeculectomy

      Purpose To map the 3-dimensional (3D) strain of the optic nerve head (ONH) in vivo after intraocular pressure (IOP) lowering by trabeculectomy (TE) and to establish associations between ONH strain and retinal sensitivity. Design Observational case series. Participants Nine patients with primary open-angle glaucoma (POAG) and 3 normal controls. Methods The ONHs of 9 subjects with POAG (pre-TE IOP: 25.3±13.9 mmHg; post-TE IOP: 11.8±8.6 mmHg) were imaged (1 eye per subject) using optical coherence tomography (OCT) (Heidelberg Spectralis, Heidelberg Engineering GmbH, Heidelberg, Germany) before (<21 days) and after (<50 days) TE. The imaging protocol ...

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    23. Enhancement of Corneal Visibility in Optical Coherence Tomography Images Using Corneal Adaptive Compensation

      Enhancement of Corneal Visibility in Optical Coherence Tomography Images Using Corneal Adaptive Compensation

      Purpose: To improve the contrast of optical coherence tomography (OCT) images of the cornea (post processing). Methods: We have recently developed standard compensation (SC) algorithms to remove light attenuation artifacts. A more recent approach, namely adaptive compensation (AC), further limited noise overamplification within deep tissue regions. AC was shown to work efficiently when all A-scan signals were fully attenuated at high depth. But in many imaging applications (e.g., OCT imaging of the cornea), such an assumption is not satisfied, which can result in strong noise overamplification. A corneal adaptive compensation (CAC) algorithm was therefore developed to overcome such limitation ...

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    24. Determinants of Optical Coherence Tomography–Derived Minimum Neuroretinal Rim Width in a Normal Chinese Population

      Determinants of Optical Coherence Tomography–Derived Minimum Neuroretinal Rim Width in a Normal Chinese Population

      Purpose. To characterize an optical coherence tomography (OCT)–derived parameter, Bruch's membrane opening–minimum rim width (BMO-MRW), and its association with demographic and clinical parameters in normal Chinese subjects. Methods. Right eyes of 466 consecutive healthy subjects from a population-based study of Singaporean Chinese underwent Cirrus OCT imaging. The retinal internal limiting membrane (ILM) and BMO were automatically delineated using the built-in Cirrus algorithm. The standard 36 interpolated radial B-scans (72 BMO points, 5° increments) of each optic nerve head were manually extracted from the central circle (3.46-mm diameter). We used Matlab to measure the shortest distance from ...

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    Shadow removal and contrast enhancement in optical coherence tomography images of the human optic nerve head Imaging of coronary artery plaques using contrast-enhanced optical coherence tomography Feature Of The Week 9/9/12: Imaging of Coronary Artery Plaques Using Contrast Enhanced Optical Coherence Tomography Intracoronary imaging using attenuation-compensated optical coherence tomography allows better visualisation of coronary artery diseases In vivo optic nerve head biomechanics: performance testing of a three-dimensional tracking algorithm Postdoctoral Fellow/Research Associate –Using Biomechanics to Predict Vision Loss Progression– National University of Singapore Feature of The Week 12/14/14: Penetrate Deeper Using Extended Source OCT Determinants of Optical Coherence Tomography–Derived Minimum Neuroretinal Rim Width in a Normal Chinese Population Feature Of The Week 05/28/2017: In Vivo 3-Dimensional Strain Mapping Confirms Large Optic Nerve Head Deformations Following Horizontal Eye Movements DRUNET: A Dilated-Residual U-Net Deep Learning Network to Digitally Stain Optic Nerve Head Tissues in Optical Coherence Tomography Images Interpretation of anatomic correlates of outer retinal bands in optical coherence tomography Optical Coherence Tomography Angiography Findings of Iris Ischemia and Reperfusion in Cytomegalovirus Panuveitis