AI Medical Compendium Topic:
Tomography, Optical Coherence

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Segmentation of Drosophila heart in optical coherence microscopy images using convolutional neural networks.

Journal of biophotonics
Convolutional neural networks (CNNs) are powerful tools for image segmentation and classification. Here, we use this method to identify and mark the heart region of Drosophila at different developmental stages in the cross-sectional images acquired b...

Automated Layer Segmentation of Retinal Optical Coherence Tomography Images Using a Deep Feature Enhanced Structured Random Forests Classifier.

IEEE journal of biomedical and health informatics
Optical coherence tomography (OCT) is a high-resolution and noninvasive imaging modality that has become one of the most prevalent techniques for ophthalmic diagnosis. Retinal layer segmentation is very crucial for doctors to diagnose and study retin...

Comparison of Machine-Learning Classification Models for Glaucoma Management.

Journal of healthcare engineering
This study develops an objective machine-learning classification model for classifying glaucomatous optic discs and reveals the classificatory criteria to assist in clinical glaucoma management. In this study, 163 glaucoma eyes were labelled with fou...

Development of an efficient algorithm for the detection of macular edema from optical coherence tomography images.

International journal of computer assisted radiology and surgery
PURPOSE: Detection of eye diseases and their treatment is a key to reduce blindness, which impacts human daily needs like driving, reading, writing, etc. Several methods based on image processing have been used to monitor the presence of macular dise...

A deep learning approach for pose estimation from volumetric OCT data.

Medical image analysis
Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its micromet...

Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model.

IEEE journal of biomedical and health informatics
Optical coherence tomography (OCT) is an imaging modality that is used extensively for ophthalmic diagnosis, near-histological visualization, and quantification of retinal abnormalities such as cysts, exudates, retinal layer disorganization, etc. Int...

Surrogate-Assisted Retinal OCT Image Classification Based on Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Optical Coherence Tomography (OCT) is beco-ming one of the most important modalities for the noninvasive assessment of retinal eye diseases. As the number of acquired OCT volumes increases, automating the OCT image analysis is becoming increasingly r...

Automated detection of preserved photoreceptor on optical coherence tomography in choroideremia based on machine learning.

Journal of biophotonics
Optical coherence tomography (OCT) can demonstrate early deterioration of the photoreceptor integrity caused by inherited retinal degeneration diseases (IRDs). A machine learning method based on random forests was developed to automatically detect co...