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Tomography, Optical Coherence

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Deep learning automatically assesses 2-µm laser-induced skin damage OCT images.

Lasers in medical science
The present study proposed a noninvasive, automated, in vivo assessment method based on optical coherence tomography (OCT) and deep learning techniques to qualitatively and quantitatively analyze the biological effects of 2-µm laser-induced skin dama...

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods.

Scientific data
Optical coherence tomography (OCT) is a non-invasive imaging technique with extensive clinical applications in ophthalmology. OCT enables the visualization of the retinal layers, playing a vital role in the early detection and monitoring of retinal d...

Noninvasive virtual biopsy using micro-registered optical coherence tomography (OCT) in human subjects.

Science advances
Histological hematoxylin and eosin-stained (H&E) tissue sections are used as the gold standard for pathologic detection of cancer, tumor margin detection, and disease diagnosis. Producing H&E sections, however, is invasive and time-consuming. While d...

Potential rapid intraoperative cancer diagnosis using dynamic full-field optical coherence tomography and deep learning: A prospective cohort study in breast cancer patients.

Science bulletin
An intraoperative diagnosis is critical for precise cancer surgery. However, traditional intraoperative assessments based on hematoxylin and eosin (H&E) histology, such as frozen section, are time-, resource-, and labor-intensive, and involve specime...

Predicting central choroidal thickness from colour fundus photographs using deep learning.

PloS one
The estimation of central choroidal thickness from colour fundus images can improve disease detection. We developed a deep learning method to estimate central choroidal thickness from colour fundus images at a single institution, using independent da...

Accuracy of generative deep learning model for macular anatomy prediction from optical coherence tomography images in macular hole surgery.

Scientific reports
This study aims to propose a generative deep learning model (GDLM) based on a variational autoencoder that predicts macular optical coherence tomography (OCT) images following full-thickness macular hole (FTMH) surgery and evaluate its clinical accur...

Explainable ensemble learning method for OCT detection with transfer learning.

PloS one
The accuracy and interpretability of artificial intelligence (AI) are crucial for the advancement of optical coherence tomography (OCT) image detection, as it can greatly reduce the manual labor required by clinicians. By prioritizing these aspects d...

Diagnostic decisions of specialist optometrists exposed to ambiguous deep-learning outputs.

Scientific reports
Artificial intelligence (AI) has great potential in ophthalmology. We investigated how ambiguous outputs from an AI diagnostic support system (AI-DSS) affected diagnostic responses from optometrists when assessing cases of suspected retinal disease. ...

Deep-learning automated quantification of longitudinal OCT scans demonstrates reduced RPE loss rate, preservation of intact macular area and predictive value of isolated photoreceptor degeneration in geographic atrophy patients receiving C3 inhibition treatment.

The British journal of ophthalmology
OBJECTIVE: To evaluate the role of automated optical coherence tomography (OCT) segmentation, using a validated deep-learning model, for assessing the effect of C3 inhibition on the area of geographic atrophy (GA); the constituent features of GA on O...

Distribution and determinants of choroidal vascularity index in healthy eyes from deep-learning choroidal analysis: a population-based SS-OCT study.

The British journal of ophthalmology
AIMS: To quantify the profiles of choroidal vascularity index (CVI) using fully artificial intelligence (AI)-based algorithm applied to swept-source optical coherence tomography (SS-OCT) images and evaluate the determinants of CVI in a population-bas...