1. Articles from hiroshi ishikawa

    1-24 of 83 1 2 3 4 »
    1. In Vivo Sublayer Analysis Of Human Retinal Inner Plexiform Layer Obtained By Visible-Light Optical Coherence Tomography

      In Vivo Sublayer Analysis Of Human Retinal Inner Plexiform Layer Obtained By Visible-Light Optical Coherence Tomography

      Purpose: Growing evidence suggests, in glaucoma, the dendritic degeneration of subpopulation of the retinal ganglion cells (RGCs) may precede RGCs soma death. Since different RGCs synapse in different IPL sublayers, visualization of the lamellar structure of the IPL could enable both clinical and fundamental advances in glaucoma understanding and management. In this pilot study, we investigated whether visible-light optical coherence tomography (vis-OCT) could detect the difference in the inner plexiform layer (IPL) sublayers thicknesses between small cohorts of healthy and glaucomatous subjects. Method: We investigated vis-OCT retinal images from nine healthy and five glaucomatous subjects. Four of the healthy subjects ...

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    2. Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography

      Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography

      Optical Coherence Tomography (OCT) is pervasive in both the research and clinical practice of Ophthalmology. However, OCT images are strongly corrupted by noise, limiting their interpretation. Current OCT denoisers leverage assumptions on noise distributions or generate targets for training deep supervised denoisers via averaging of repeat acquisitions. However, recent self-supervised advances allow the training of deep denoising networks using only repeat acquisitions without clean targets as ground truth, reducing the burden of supervised learning. Despite the clear advantages of self-supervised methods, their use is precluded as OCT shows strong structural deformations even between sequential scans of the same subject due ...

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    3. Attention-guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association using Volumetric Images

      Attention-guided 3D-CNN Framework for Glaucoma Detection and Structural-Functional Association using Volumetric Images

      The direct analysis of 3D Optical Coherence Tomography (OCT) volumes enables deep learning models (DL) to learn spatial structural information and discover new bio-markers that are relevant to glaucoma. Downsampling 3D input volumes is the state-of-art solution to accommodate for the limited number of training volumes as well as the available computing resources. However, this limits the network's ability to learn from small retinal structures in OCT volumes. In this paper, our goal is to improve the performance by providing guidance to DL model during training in order to learn from finer ocular structures in 3D OCT volumes. Therefore ...

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    4. Improved Denoising of Optical Coherence Tomography via Repeated Acquisitions and Unsupervised Deep Learning

      Improved Denoising of Optical Coherence Tomography via Repeated Acquisitions and Unsupervised Deep Learning

      Purpose : Optical Coherence Tomography (OCT) is widely used, yet its interpretation is confounded by strong speckle noise. Previous denoising methods make strong assumptions on noise characteristics and struggle to retain fine structure. We present a data-driven registration and denoising method which vastly improves image fidelity while requiring only repeated noisy acquisitions of individual subjects. Methods : Noise2Noise is an unsupervised denoising approach for repeatedly acquired noisy images (Lehtinen, ICML , 2018). By training a convolutional neural network on noisy image pairs with zero-mean noise, the mean of the clean image distribution is learned. However, repeats are assumed to vary only in noise ...

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    5. Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes

      Dueling Deep Q-Network for Unsupervised Inter-frame Eye Movement Correction in Optical Coherence Tomography Volumes

      In optical coherence tomography (OCT) volumes of retina, the sequential acquisition of the individual slices makes this modality prone to motion artifacts, misalignments between adjacent slices being the most noticeable. Any distortion in OCT volumes can bias structural analysis and influence the outcome of longitudinal studies. On the other hand, presence of speckle noise that is characteristic of this imaging modality, leads to inaccuracies when traditional registration techniques are employed. Also, the lack of a well-defined ground truth makes supervised deep-learning techniques ill-posed to tackle the problem. In this paper, we tackle these issues by using deep reinforcement learning to ...

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    6. ASSESSING THE ABILITY OF PREOPERATIVE QUANTITATIVE SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHY CHARACTERISTICS TO PREDICT VISUAL OUTCOME IN IDIOPATHIC MACULAR HOLE SURGERY

      ASSESSING THE ABILITY OF PREOPERATIVE QUANTITATIVE SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHY CHARACTERISTICS TO PREDICT VISUAL OUTCOME IN IDIOPATHIC MACULAR HOLE SURGERY

      Purpose: To determine which spectral domain optical coherence tomography biomarkers of idiopathic macular hole (MH) correlate with the postoperative best-corrected visual acuity (BCVA) in anatomically closed MH. Methods: Retrospective analysis of spectral domain optical coherence tomography scans of 44 patients presenting with MH followed for a mean of 17 months. Widths of MH aperture, base, and ellipsoid zone disruption were calculated from presenting foveal spectral domain optical coherence tomography B-scans. Macular hole base area and ellipsoid zone disruption area were calculated through the custom in-house software. Results: Poorer postoperative BCVA correlated with increased preoperative choroidal hypertransmission (r = 0.503, P ...

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    7. Retinal blood flow reduction in normal-tension glaucoma with single-hemifield damage by Doppler optical coherence tomography

      Retinal blood flow reduction in normal-tension glaucoma with single-hemifield damage by Doppler optical coherence tomography

      Aims To evaluate the associations between retinal blood flow (RBF) and optical coherence tomography (OCT) structural measurements in normal-tension glaucoma (NTG) eyes with single-hemifield visual field (VF) damage by the Doppler OCT. Methods The Doppler OCT was used to measure temporal artery (TA) RBF and temporal vein (TV) RBF. Retinal nerve fibre layer thickness (RNFLT) was measured by spectral-domain OCT. Results Forty-three consecutive eyes of 43 patients with NTG with VF defect confined to a single hemifield and 24 eyes of 24 age-matched healthy subjects were studied. TA and TV RBF and RNFLT were reduced in the damaged hemisphere compared ...

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    8. 3D-CNN for Glaucoma Detection Using Optical Coherence Tomography

      3D-CNN for Glaucoma Detection Using Optical Coherence Tomography

      The large size of raw 3D optical coherence tomography (OCT) volumes poses challenges for deep learning methods as it cannot be accommodated on a single GPU in its original resolution. The direct analysis of these volumes however, provides advantages such as circumventing the need for the segmentation of retinal structures. Previously, a deep learning (DL) approach was proposed for the detection of glaucoma directly from 3D OCT volumes, where the volumes were significantly downsampled first. In this paper, we propose an end-to-end DL model for the detection of glaucoma that doubles the number of input voxels of the previously proposed ...

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    9. Speckle reduction in visible-light optical coherence tomography using scan modulation

      Speckle reduction in visible-light optical coherence tomography using scan modulation

      We present a technique to reduce speckle in visible-light optical coherence tomography (vis-OCT) that preserves fine structural details and is robust against sample motion. Specifically, we locally modulate B-scans orthogonally to their axis of acquisition. Such modulation enables acquisition of uncorrelated speckle patterns from similar anatomical locations, which can be averaged to reduce speckle. To verify the effectiveness of speckle reduction, we performed in-vivo retinal imaging using modulated raster and circular scans in both mice and humans. We compared speckle-reduced vis-OCT images with the images acquired with unmodulated B-scans from the same anatomical locations. We compared contrast-to-noise ratio (CNR) and ...

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    10. Inference of visual field test performance from OCT volumes using deep learning

      Inference of visual field test performance from OCT volumes using deep learning

      Visual field tests (VFT) are pivotal for glaucoma diagnosis and conducted regularly to monitor disease progression. Here we address the question to what degree aggregate VFT measurements such as Visual Field Index (VFI) and Mean Deviation (MD) can be inferred from Optical Coherence Tomography (OCT) scans of the Optic Nerve Head (ONH) or the macula. Accurate inference of VFT measurements from OCT could reduce examination time and cost. We propose a novel 3D Convolutional Neural Network (CNN) for this task and compare its accuracy with classical machine learning (ML) algorithms trained on common, segmentation-based OCT, features employed for glaucoma diagnostics ...

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    11. A feature agnostic approach for glaucoma detection in OCT volumes

      A feature agnostic approach for glaucoma detection in OCT volumes

      Optical coherence tomography (OCT) based measurements of retinal layer thickness, such as the retinal nerve fibre layer (RNFL) and the ganglion cell with inner plexiform layer (GCIPL) are commonly employed for the diagnosis and monitoring of glaucoma. Previously, machine learning techniques have relied on segmentation-based imaging features such as the peripapillary RNFL thickness and the cup-to-disc ratio. Here, we propose a deep learning technique that classifies eyes as healthy or glaucomatous directly from raw, unsegmented OCT volumes of the optic nerve head (ONH) using a 3D Convolutional Neural Network (CNN). We compared the accuracy of this technique with various feature-based ...

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    12. Designing visible-light optical coherence tomography towards clinics

      Designing visible-light optical coherence tomography towards clinics

      Background: The capabilities of visible-light optical coherence tomography (vis-OCT) in noninvasive anatomical and functional retinal imaging have been demonstrated by multiple groups in both rodents and healthy human subjects. Translating laboratory prototypes to an integrated clinical-environment-friendly system is required to explore the full potential of vis-OCT in disease management. Methods: We developed and optimized a portable vis-OCT system for human retinal imaging in clinical settings. We acquired raster- and circular-scan images from both healthy and diseased human eyes. Results: The new vis-OCT provided high-quality retinal images of both subjects without any known eye diseases and patients with various retinal diseases ...

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    13. Retinal optical coherence tomography image enhancement via deep learning

      Retinal optical coherence tomography image enhancement via deep learning

      Optical coherence tomography (OCT) images of the retina are a powerful tool for diagnosing and monitoring eye disease. However, they are plagued by speckle noise, which reduces image quality and reliability of assessment. This paper introduces a novel speckle reduction method inspired by the recent successes of deep learning in medical imaging. We present two versions of the network to reflect the needs and preferences of different end-users. Specifically, we train a convolution neural network to denoise cross-sections from OCT volumes of healthy eyes using either (1) mean-squared error, or (2) a generative adversarial network (GAN) with Wasserstein distance and ...

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    14. Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm

      Classification of healthy and diseased retina using SD-OCT imaging and Random Forest algorithm

      In this paper, we propose a novel classification model for automatically identifying individuals with age-related macular degeneration (AMD) or Diabetic Macular Edema (DME) using retinal features from Spectral Domain Optical Coherence Tomography (SD-OCT) images. Our classification method uses retinal features such as the thickness of the retina and the thickness of the individual retinal layers, and the volume of the pathologies such as drusen and hyper-reflective intra-retinal spots. We extract automatically, ten clinically important retinal features by segmenting individual SD-OCT images for classification purposes. The effectiveness of the extracted features is evaluated using several classification methods such as Random Forrest ...

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    15. An Automated Method for Choroidal Thickness Measurement from Enhanced Depth Imaging Optical Coherence Tomography Images

      An Automated Method for Choroidal Thickness Measurement from Enhanced Depth Imaging Optical Coherence Tomography Images

      The choroid is vascular tissue located underneath the retina and supplies oxygen to the outer retina; any damage to this tissue can be a precursor to retinal diseases. This paper presents an automated method of choroidal segmentation from enhanced depth imaging optical coherence tomography (EDI-OCT) images. The Dijkstra shortest path algorithm is used to segment the choroid-sclera interface (CSI), the outermost border of the choroid. A novel intensity-normalisation technique that is based on the depth of the choroid is used to equalise the intensity of all non-vessel pixels in the choroid region. The outer boundary of choroidal vessel and CSI ...

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    16. Signal normalization among multiple optical coherence tomography devices

      Signal normalization among multiple optical coherence tomography devices

      The present disclosure is directed to systems and methods for normalizing an image of an eye among multiple optical coherence tomography (OCT) devices. The system can receive an OCT image and generate a normalized OCT image. The system is configured to normalize a sample density of the received image, normalize an amount of noise using a suitable noise reduction technique, normalize a distribution of signal amplitudes of the image, and then normalize a signal quality of the image. The resulting normalized image of the eye can then be used in the comparison among OCT images taken from multiple OCT devices.

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    17. Signal Normalization Reduces Image Appearance Disparity Among Multiple Optical Coherence Tomography Devices

      Signal Normalization Reduces Image Appearance Disparity Among Multiple Optical Coherence Tomography Devices

      Purpose : To assess the effect of the previously reported optical coherence tomography (OCT) signal normalization method on reducing the discrepancies in image appearance among spectral-domain OCT (SD-OCT) devices. Methods : Healthy eyes and eyes with various retinal pathologies were scanned at the macular region using similar volumetric scan patterns with at least two out of three SD-OCT devices at the same visit (Cirrus HD-OCT, Zeiss, Dublin, CA; RTVue, Optovue, Fremont, CA; and Spectralis, Heidelberg Engineering, Heidelberg, Germany). All the images were processed with the signal normalization. A set of images formed a questionnaire with 24 pairs of cross-sectional images from each ...

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    18. Optic Nerve Head Measurements With Optical Coherence Tomography: A Phantom-Based Study Reveals Differences Among Clinical Devices

      Optic Nerve Head Measurements With Optical Coherence Tomography: A Phantom-Based Study Reveals Differences Among Clinical Devices

      Purpose : Optical coherence tomography (OCT) can monitor for glaucoma by measuring dimensions of the optic nerve head (ONH) cup and disc. Multiple clinical studies have shown that different OCT devices yield different estimates of retinal dimensions. We developed phantoms mimicking ONH morphology as a new way to compare ONH measurements from different clinical OCT devices. Methods : Three phantoms were fabricated to model the ONH: One normal and two with glaucomatous anatomies. Phantoms were scanned with Stratus, RTVue, and Cirrus clinical devices, and with a laboratory OCT system as a reference. We analyzed device-reported ONH measurements of cup-to-disc ratio (CDR) and ...

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    19. Virtual Averaging Making Nonframe-Averaged Optical Coherence Tomography Images Comparable to Frame-Averaged Images

      Virtual Averaging Making Nonframe-Averaged Optical Coherence Tomography Images Comparable to Frame-Averaged Images

      Purpose : Developing a novel image enhancement method so that nonframe-averaged optical coherence tomography (OCT) images become comparable to active eye-tracking frame-averaged OCT images. Methods : Twenty-one eyes of 21 healthy volunteers were scanned with noneye-tracking nonframe-averaged OCT device and active eye-tracking frame-averaged OCT device. Virtual averaging was applied to nonframe-averaged images with voxel resampling and adding amplitude deviation with 15-time repetitions. Signal-to-noise (SNR), contrast-to-noise ratios (CNR), and the distance between the end of visible nasal retinal nerve fiber layer (RNFL) and the foveola were assessed to evaluate the image enhancement effect and retinal layer visibility. Retinal thicknesses before and after processing ...

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    20. Predicting Development of Glaucomatous Visual Field Conversion Using Baseline Fourier-Domain Optical Coherence Tomography

      Predicting Development of Glaucomatous Visual Field Conversion Using Baseline Fourier-Domain Optical Coherence Tomography

      Purpose To predict the development of glaucomatous visual field (VF) defects using Fourier-domain optical coherence tomography (FD-OCT) measurements at baseline visit. Design Multi-center longitudinal observational study. Glaucoma suspects and pre-perimetric glaucoma participants in the Advanced Imaging for Glaucoma Study. Methods The optic disc, the peripapillary retinal nerve fiber layer (NFL), and macular ganglion cell complex (GCC) were imaged with FD-OCT VF was assessed every 6 months. Conversion to perimetric glaucoma was defined by VF pattern standard deviation (PSD) or glaucoma hemifield test (GHT) outside normal limits on 3 consecutive tests. Hazard ratios were calculated with the Cox proportional hazard model ...

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    21. Retinal imaging with en face and cross-sectional optical coherence tomography delineates outer retinal changes in cancer-associated retinopathy secondary to Merkel cell carcinoma

      Retinal imaging with en face and cross-sectional optical coherence tomography delineates outer retinal changes in cancer-associated retinopathy secondary to Merkel cell carcinoma

      Background The study aims to correlate Fourier-domain optical coherence tomography (FD-OCT) with Goldmann visual field (GVF) to show the photoreceptor (PR) structure and function relationship in the first described case of cancer-associated retinopathy (CAR) from Merkel cell carcinoma. Findings A case study of a patient with CAR who was imaged with serial GVF and FD-OCT over a 2-year period was carried out. En face images were created using a custom algorithm from the volumetric Fourier-domain OCT scans at the PR level. The areas of decreased PR reflectivity on the en face images were compared with GVF obtained at the same ...

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    22. Histogram Matching Extends Acceptable Signal Strength Range on Optical Coherence Tomography Images

      Histogram Matching Extends Acceptable Signal Strength Range on Optical Coherence Tomography Images

      Purpose. We minimized the influence of image quality variability, as measured by signal strength (SS), on optical coherence tomography (OCT) thickness measurements using the histogram matching (HM) method. Methods. We scanned 12 eyes from 12 healthy subjects with the Cirrus HD-OCT device to obtain a series of OCT images with a wide range of SS (maximal range, 1–10) at the same visit. For each eye, the histogram of an image with the highest SS (best image quality) was set as the reference. We applied HM to the images with lower SS by shaping the input histogram into the reference ...

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    23. In Vivo Three-Dimensional Characterization of the Healthy Human Lamina Cribrosa with Adaptive Optics Spectral-Domain Optical Coherence Tomography

      In Vivo Three-Dimensional Characterization of the Healthy Human Lamina Cribrosa with Adaptive Optics Spectral-Domain Optical Coherence Tomography

      Purpose: To characterize the in vivo 3D lamina cribrosa (LC) microarchitecture of healthy eyes using adaptive optics spectral-domain optical coherence tomography (AO-SDOCT). Methods: One randomly selected eye from each of 18 healthy subjects was scanned with Cirrus HD-OCT and AO-SDOCT centered on the optic nerve head. LC microarchitecture, imaged by the later device, was semi-automatically segmented and quantified for connective tissue volume fraction (CTVF), beam thickness, pore diameter, pore area and pore aspect ratio. The LC was assessed in central and peripheral regions of equal areas, quadrants and with depth. A linear mixed-effects model weighted by the fraction of visible ...

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    24. Intra- and Inter-visit Reproducibility of Ganglion Cell – Inner Plexiform Layer Measurements Using Handheld Optical Coherence Tomography in Children with Optic Pathway Gliomas

      Intra- and Inter-visit Reproducibility of Ganglion Cell – Inner Plexiform Layer Measurements Using Handheld Optical Coherence Tomography in Children with Optic Pathway Gliomas

      Purpose To determine the intra- and inter-visit reproducibility of ganglion cell-inner plexiform layer thickness measures using handheld optical coherence tomography (OCT) in sedated children with optic pathway gliomas and/or Neurofibromatosis type 1 (NF1). Design Prospective longitudinal cohort study Methods Children with sporadic optic pathway gliomas and/or NF1 who had ≥ 2 volumes acquired over the macula using handheld OCT during sedation for a clinically indicated MRI were eligible for the intra-visit cohort. Children with repeat handheld OCT imaging within 6 months were eligible for the inter-visit cohort. Total retinal thickness and ganglion cell-inner plexiform layer thickness were measured using ...

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