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3 articles for “Optical coherence tomography (OCT)”
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Photonic Diagnostics: Harnessing Optical Sensing for Non-Invasive Assessment of Coronary Obstruction
Abstract: Cardiovascular diseases (CVDs) remain the leading cause of mortality globally, with coronary artery blockages primarily atherosclerosis representing a critical challenge. The gold standard for diagnosing coronary artery disease remains invasive coronary angiography, a procedure that, while precise, carries inherent patient risks, high costs, and logistical burdens. Optical sensors, leveraging the principles of light-tissue interaction, offer real-time, high-resolution insights into vascular health, paving the way for early detection of arterial stenoses …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 25–30 Read article
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Survey on Retinal OCT Image Preprocessing, Segmentation, and Deep Learning Based Classification
Abstract: Optical coherence tomography (OCT) is a non-invasive technique that generates high-resolution, detailed cross-sectional images of biological tissues. By utilizing low-coherence interferometry, OCT enables visualization of tissue microstructure with micron-scale resolution, making it useful in various medical fields such as ophthalmology, cardiology, and dermatology. In ophthalmology, OCT is extensively used for diagnosing and monitoring retinal diseases like macular degeneration and diabetic retinopathy, allowing doctors to assess changes in tissue morphology over …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Refining Retinal Layer Segmentation in OCT Imaging with Advanced Techniques and Clinical Applications
Abstract: Segmenting retinal layers from Optical Coherence Tomography (OCT) pictures entails locating and separating different retinal layers to offer comprehensive anatomical and pathological information. Age-related macular degeneration, diabetic retinopathy, and glaucoma are among the retinal illnesses for which this procedure is crucial for diagnosis and follow-up. By utilizing preprocessing techniques to improve image quality and applying advanced algorithms—such as intensity-based, gradient-based, and texture-based methods—alongside deep learning approaches, clinicians can accurately measure …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 01–06 Read article