AIMC Topic: Tomography, Optical Coherence

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The Retinal Age Gap as a Marker of Accelerated Aging in the Early Course of Schizophrenia.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Given the available findings confirming accelerated brain aging in schizophrenia (SZ), we conducted a study aimed at verifying whether quantitative retinal morphological data enable age prediction and whether schizophrenia ...

[Focusing on the challenges and opportunities of optical coherence tomography in the diagnosis and treatment of fundus diseases].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Optical coherence tomography (OCT), with its advantages of non-invasiveness, non-contact, rapid imaging, and high resolution, has become an indispensable core imaging tool in the diagnosis and treatment of fundus diseases. It provides clinicians with...

Artificial intelligence-based identification of thin-cap fibroatheromas and clinical outcomes: the PECTUS-AI study.

European heart journal
BACKGROUND AND AIMS: Coronary thin-cap fibroatheromas (TCFA) are associated with adverse outcome, but identification of TCFA requires expertise and is highly time-demanding. This study evaluated the utility of artificial intelligence (AI) for TCFA id...

Validation of a deep learning model for the automated detection and quantification of cystoid macular oedema on optical coherence tomography in patients with retinitis pigmentosa.

Acta ophthalmologica
PURPOSE: Accurate assessment of cystoid macular oedema (CMO) in patients with retinitis pigmentosa (RP) on spectral-domain optical coherence tomography (SD-OCT) is crucial for tracking disease progression and may serve as a therapeutic endpoint. Manu...

Enhancing pathological myopia diagnosis: a bimodal artificial intelligence approach integrating fundus and optical coherence tomography imaging for precise atrophy, traction and neovascularisation grading.

The British journal of ophthalmology
BACKGROUND: Pathological myopia (PM) has emerged as a leading cause of global visual impairment, early detection and precise grading of PM are crucial for timely intervention. The atrophy, traction and neovascularisation (ATN) system is applied to de...

Diabetic retinopathy detection from fundus images: A wide survey from grading to segmentation of lesions.

Computers in biology and medicine
Diabetes is one of the most common diseases worldwide and requires accurate diagnosis. Patients with diabetes are often affected by diabetic retinopathy (DR), which can lead to low vision, vision loss, or blindness. Therefore, a robust computer-aided...

AMeta-FD: Adversarial Meta-learning for Few-shot retinal OCT image Despeckling.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Speckle noise in Optical coherence tomography (OCT) images compromises the performance of image analysis tasks such as retinal layer boundary detection. Deep learning algorithms have demonstrated the advantage of being more cost-effective and robust ...

Performance of Artificial Intelligence-Based Models for Epiretinal Membrane Diagnosis: A Systematic Review and Meta-Analysis.

American journal of ophthalmology
TOPIC: Epiretinal membrane (ERM) can impair central vision by forming a pre-retinal fibrous layer on the inner retina. Artificial intelligence (AI)-based tools may streamline ERM diagnosis, but their overall performance and factors affecting accuracy...

Integration of proteomics and artificial intelligence-driven OCT biomarker analysis in central retinal vein occlusion.

Experimental eye research
Retinal OCT biomarker analysis by artificial intelligence (AI) has not previously been integrated with proteomics. Here, we combined the two techniques to elucidate novel molecular mechanisms in central retinal vein occlusion (CRVO). Proteomic data o...