1. Articles from Andreas K. Maier

    1-5 of 5
    1. OCT-OCTA segmentation: combining structural and blood flow information to segment Bruch's membrane

      OCT-OCTA segmentation: combining structural and blood flow information to segment Bruch's membrane

      In this paper we present a fully automated graph-based segmentation algorithm that jointly uses optical coherence tomography (OCT) and OCT angiography (OCTA) data to segment Bruch's membrane (BM). This is especially valuable in cases where the spatial correlation between BM, which is usually not visible on OCT scans, and the retinal pigment epithelium (RPE), which is often used as a surrogate for segmenting BM, is distorted by pathology. We validated the performance of our proposed algorithm against manual segmentation in a total of 18 eyes from healthy controls and patients with diabetic retinopathy (DR), non-exudative age-related macular degeneration (AMD ...

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    2. Efficient and high accuracy 3-D OCT angiography motion correction in pathology

      Efficient and high accuracy 3-D OCT angiography motion correction in pathology

      We describe a novel method for non-rigid 3-D motion correction of orthogonally raster-scanned optical coherence tomography angiography volumes. This is the first approach that aligns predominantly axial structural features such as retinal layers as well as transverse angiographic vascular features in a joint optimization. Combined with orthogonal scanning and favorization of kinematically more plausible displacements, subpixel alignment and micrometer-scale distortion correction is achieved in all 3 dimensions. As no specific structures are segmented, the method is by design robust to pathologic changes. Furthermore, the method is designed for highly parallel implementation and short runtime, allowing its integration into clinical workflow ...

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    3. Deep OCT Angiography Image Generation for Motion Artifact Suppression

      Deep OCT Angiography Image Generation for Motion Artifact Suppression

      Eye movements, blinking and other motion during the acquisition of optical coherence tomography (OCT) can lead to artifacts, when processed to OCT angiography (OCTA) images. Affected scans emerge as high intensity (white) or missing (black) regions, resulting in lost information. The aim of this research is to fill these gaps using a deep generative model for OCT to OCTA image translation relying on a single intact OCT scan. Therefore, a U-Net is trained to extract the angiographic information from OCT patches. At inference, a detection algorithm finds outlier OCTA scans based on their surroundings, which are then replaced by the ...

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    4. Temporal and Volumetric Denoising via Quantile Sparse Image (QuaSI) Prior in Optical Coherence Tomography and Beyond

      Temporal and Volumetric Denoising via Quantile Sparse Image (QuaSI) Prior in Optical Coherence Tomography and Beyond

      This paper introduces an universal and structure-preserving regularization term, called quantile sparse image (QuaSI) prior. The prior is suitable for denoising images from various medical image modalities. We demonstrate its effectivness on volumetric optical coherence tomography (OCT) and computed tomography (CT) data, which show differnt noise and image characteristics. OCT offers high-resolution scans of the human retina but is inherently impaired by speckle noise. CT on the other hand has a lower resolution and shows high-frequency noise. For purpose of denoising, we propose a variational framework based on the QuaSI prior and a Huber data fidelity model that can handle ...

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    5. QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

      QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data

      Optical coherence tomography (OCT) enables high-resolution and non-invasive 3D imaging of the human retina but is inherently impaired by speckle noise. This paper introduces a spatio-temporal denoising algorithm for OCT data on a B-scan level using a novel quantile sparse image (QuaSI) prior. To remove speckle noise while preserving image structures of diagnostic relevance, we implement our QuaSI prior via median filter regularization coupled with a Huber data fidelity model in a variational approach. For efficient energy minimization, we develop an alternating direction method of multipliers (ADMM) scheme using a linearization of median filtering. Our spatio-temporal method can handle both ...

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    1-5 of 5
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  2. Topics in the News

    1. (4 articles) Massachusetts Institute of Technology
    2. (4 articles) University of Erlangen
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    QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Data Temporal and Volumetric Denoising via Quantile Sparse Image (QuaSI) Prior in Optical Coherence Tomography and Beyond Deep OCT Angiography Image Generation for Motion Artifact Suppression Efficient and high accuracy 3-D OCT angiography motion correction in pathology OCT-OCTA segmentation: combining structural and blood flow information to segment Bruch's membrane Structural abnormalities associated with glaucoma using swept-source optical coherence tomography in patients with systemic sclerosis Clinical presentation does not affect acute mechanical performance of the Novolimus-eluting bioresorbable vascular scaffold as assessed by optical coherence tomography Evaluating optical coherence tomography (OCT) findings as potential biomarkers in central nervous system (CNS) lymphoma with or without ocular involvement Polarization sensitive optical coherence tomography with single input for imaging depth-resolved collagen organizations Etanercept Therapy for Nails Psoriasis Monitoring With Noninvasive Imaging The Use of Optical Coherence Tomography to Asscess Water Transport Through The Urothelium of The Porcine Bladder Evaluation of the Effect of Covid-19 on Optic Disk and Macula with OCT and OCT-Angiography