AIMC Topic: Tomography, Optical Coherence
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Glaucoma diagnosis using multi-feature analysis and a deep learning technique.
Scientific reports
May 16, 2022
In this study, we aimed to facilitate the current diagnostic assessment of glaucoma by analyzing multiple features and introducing a new cross-sectional optic nerve head (ONH) feature from optical coherence tomography (OCT) images. The data (n = 100 ...
Therapeutic response in the HAWK and HARRIER trials using deep learning in retinal fluid volume and compartment analysis.
Eye (London, England)
May 6, 2022
OBJECTIVES: To assess the therapeutic response to brolucizumab and aflibercept by deep learning/OCT-based analysis of macular fluid volumes in neovascular age-related macular degeneration.
Validation of Soft Labels in Developing Deep Learning Algorithms for Detecting Lesions of Myopic Maculopathy From Optical Coherence Tomographic Images.
Asia-Pacific journal of ophthalmology (Philadelphia, Pa.)
May 1, 2022
PURPOSE: It is common for physicians to be uncertain when examining some images. Models trained with human uncertainty could be a help for physicians in diagnosing pathologic myopia.
Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.
European journal of ophthalmology
Apr 27, 2022
PURPOSE: Artificial intelligence (AI) can detect diabetic macular edema (DME) from optical coherence tomography (OCT) images. We aimed to evaluate the performance of deep learning neural networks in DME detection.
Towards more efficient ophthalmic disease classification and lesion location via convolution transformer.
Computer methods and programs in biomedicine
Apr 27, 2022
OBJECTIVE: A retina optical coherence tomography (OCT) image differs from a traditional image due to its significant speckle noise, irregularity, and inconspicuous features. A conventional deep learning architecture cannot effectively improve the cla...
Artificial intelligence based detection of age-related macular degeneration using optical coherence tomography with unique image preprocessing.
European journal of ophthalmology
Apr 25, 2022
PURPOSE: The aim of the study is to improve the accuracy of age related macular degeneration (AMD) disease in its earlier phases with proposed Capsule Network (CapsNet) architecture trained on speckle noise reduced spectral domain optical coherence t...
Recent Advanced Deep Learning Architectures for Retinal Fluid Segmentation on Optical Coherence Tomography Images.
Sensors (Basel, Switzerland)
Apr 15, 2022
With non-invasive and high-resolution properties, optical coherence tomography (OCT) has been widely used as a retinal imaging modality for the effective diagnosis of ophthalmic diseases. The retinal fluid is often segmented by medical experts as a p...
Diagnosis of Retinal Diseases Based on Bayesian Optimization Deep Learning Network Using Optical Coherence Tomography Images.
Computational intelligence and neuroscience
Apr 15, 2022
Retinal abnormalities have emerged as a serious public health concern in recent years and can manifest gradually and without warning. These diseases can affect any part of the retina, causing vision impairment and indeed blindness in extreme cases. T...
Cervical optical coherence tomography image classification based on contrastive self-supervised texture learning.
Medical physics
Apr 13, 2022
BACKGROUND: Cervical cancer (CC) seriously affects the health of the female reproductive system. Optical coherence tomography (OCT) emerged as a noninvasive, high-resolution imaging technology for cervical disease detection. However, OCT image annota...
Correlation of choroidal thickness with age in healthy subjects: automatic detection and segmentation using a deep learning model.
International ophthalmology
Apr 5, 2022
PROPOSE: The proposed deep learning model with a mask region-based convolutional neural network (Mask R-CNN) can predict choroidal thickness automatically. Changes in choroidal thickness with age can be detected with manual measurements. In this stud...
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