AIMC Topic: Tomography, Optical Coherence

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Deep learning to distinguish Best vitelliform macular dystrophy (BVMD) from adult-onset vitelliform macular degeneration (AVMD).

Scientific reports Jul 26, 2022
Initial stages of Best vitelliform macular dystrophy (BVMD) and adult vitelliform macular dystrophy (AVMD) harbor similar blue autofluorescence (BAF) and optical coherence tomography (OCT) features. Nevertheless, BVMD is characterized by a worse fina...
Deep Learning Visual Acuity Humans Adult Bestrophins Vitelliform Macular Dystrophy Tomography, Optical Coherence Neoplasm Recurrence, Local
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HCTNet: A Hybrid ConvNet-Transformer Network for Retinal Optical Coherence Tomography Image Classification.

Biosensors Jul 20, 2022
Automatic and accurate optical coherence tomography (OCT) image classification is of great significance to computer-assisted diagnosis of retinal disease. In this study, we propose a hybrid ConvNet-Transformer network (HCTNet) and verify the feasibil...
Neural Networks, Computer Tomography, Optical Coherence Retina
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Fast and Efficient Method for Optical Coherence Tomography Images Classification Using Deep Learning Approach.

Sensors (Basel, Switzerland) Jun 21, 2022
The use of optical coherence tomography (OCT) in medical diagnostics is now common. The growing amount of data leads us to propose an automated support system for medical staff. The key part of the system is a classification algorithm developed with ...
Macular Edema Diabetic Retinopathy Deep Learning Humans Neural Networks, Computer Tomography, Optical Coherence
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Multi-class retinal fluid joint segmentation based on cascaded convolutional neural networks.

Physics in medicine and biology Jun 15, 2022
. Retinal fluid mainly includes intra-retinal fluid (IRF), sub-retinal fluid (SRF) and pigment epithelial detachment (PED), whose accurate segmentation in optical coherence tomography (OCT) image is of great importance to the diagnosis and treatment ...
Retina Image Processing, Computer-Assisted Tomography, Optical Coherence Neural Networks, Computer
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Automatic segmentation of multitype retinal fluid from optical coherence tomography images using semisupervised deep learning network.

The British journal of ophthalmology Jun 13, 2022
BACKGROUND/AIMS: To develop and validate a deep learning model for automated segmentation of multitype retinal fluid using optical coherence tomography (OCT) images.
Deep Learning Tomography, Optical Coherence Retina Subretinal Fluid Humans Retrospective Studies
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Automatic assessment of calcified plaque and nodule by optical coherence tomography adopting deep learning model.

The international journal of cardiovascular imaging Jun 7, 2022
Optical coherence tomography (OCT) has become the best imaging tool to assess calcified plaque and nodule. However, every OCT pullback has numerous images, and artificial analysis requires too much time and energy. Thus, it is unsuitable for clinical...
Humans Deep Learning Plaque, Atherosclerotic Predictive Value of Tests Tomography, Optical Coherence
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Predicting persistent central serous chorioretinopathy using multiple optical coherence tomographic images by deep learning.

Scientific reports Jun 4, 2022
We sought to predict whether central serous chorioretinopathy (CSC) will persist after 6 months using multiple optical coherence tomography (OCT) images by deep convolutional neural network (CNN). This was a multicenter, retrospective, cohort study. ...
Deep Learning Cohort Studies Humans Retrospective Studies Fluorescein Angiography Central Serous Chorioretinopathy Choroid Tomography, Optical Coherence
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Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning.

Scientific reports May 31, 2022
Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challenge. To address this, we developed a forward-view endoscopic optical coherence tomography (OCT) syst...
Tomography, Optical Coherence Needles Anesthesia, Epidural Animals Swine Epidural Space Deep Learning
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A lightweight deep learning model for automatic segmentation and analysis of ophthalmic images.

Scientific reports May 20, 2022
Detection, diagnosis, and treatment of ophthalmic diseases depend on extraction of information (features and/or their dimensions) from the images. Deep learning (DL) model are crucial for the automation of it. Here, we report on the development of a ...
Deep Learning Angiography Image Processing, Computer-Assisted Reproducibility of Results Tomography, Optical Coherence Retina
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Automatic Segmentation and Measurement of Choroid Layer in High Myopia for OCT Imaging Using Deep Learning.

Journal of digital imaging May 17, 2022
Automatic segmentation and measurement of the choroid layer is useful in studying of related fundus diseases, such as diabetic retinopathy and high myopia. However, most algorithms are not helpful for choroid layer segmentation due to its blurred bou...
Choroid Tomography, Optical Coherence Myopia Deep Learning Diabetic Retinopathy Humans
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