Tag: Ophthalmology

Deep Learning in Ophthalmology

Recent works suggest novel deep learning tools for detection, segmentation and characterization of eye disorders. Accurate segmentation of retinal fundus lesions and anomalies in imaging

Classification and Segmentation of Dendritic Cells

Dry eye disease (DED) is one of the most common ophthalmic disorders. Inflammation of the ocular surface is controlled by corneal antigen-presenting cells called dendritic

Biometric Detection and Measurement

Eyeglasses have been with us since the 13th century, although mass production and affordability to commoner (aside from clerics, scholars and wealthy people) has begun

Degenerative Diseases Detection in the Eye

Modern imaging knows how to capture an image to see through the eye tissue transparency and inspect retina, vasculature and neural tissue: this phenomenon is

Temporary pediatric strabismus in newborn baby

Image processing for pediatric strabismus

Strabismus is a disorder in which the eyes are not properly aligned and point to different directions. When this happens, the “straighter” eye becomes more dominant and the

ROP - Vessel tortuosity in Retinopathy of Prematurity

ROP: Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a leading cause of blindness in infants. ROP (or Terry syndrome) is a disease of the eye affecting prematurely-born, low

Eyelid Drooping – Blepharoptosis

Blepharoptosis, also known as ptosis, is a drooping of the upper eyelid causing a narrowing of the palpebral fissure (or palpebral aperture), which is the

Retinal images enhancement

Image enhancement of retinal structures has the potential to facilitate diagnosis of several eye diseases. Retinal disease diagnosis and monitoring often requires very delicate analysis

Pattern Recognition for Lens Markings Detection

Lens marking refers to the placement of temporary and/or permanent marking, semi-visible laser engraving for the use of lens identification and trademarks, and accurate placement

Tear film formation and meibomian glands

Meibomian gland dysfunction detection

Meibomian gland dysfunction is often seen as an early stage of dry eye syndrome. Indeed, Meibomian glands play a significant role in tears production by

Glaucoma, a high intraocular pressure (IOP) pathology, leading to damage of the optic nerve, can be better detected using deep learning techniques. When it detects the optical disc (the visible section of the optic nerve), the deep learning algorithm helps assess glaucoma in an automated way, starting from the region of interest and providing a reliable probability for the disease, which the physician will use to support both diagnosis and treatment decisions.

Retinal Detachment Detection

Retinal detachment occurs when part of the retina detaches itself from the pigmented cell layer of the RPE, depriving itself of blood and nutrition: this

Spectral Domain Optical Coherence Tomography (SD-OCT)

Retinal inner layers segmentation

OCT is the only method that can perform noninvasive imaging with non-ionizing radiation and offering relatively good resolution. That is why it has become a

Diabetic retinopathy screening and microaneurysm detection

Diabetic Retinopathy (DR) is a leading cause of blindness, especially among adults and even more among the elderly segments of the population. It is associated

Retinal images taken with mobile cameras

Portable cameras able to help ophthalmologists have been a desired solution for a long time. Among the reasons for the need of an additional device

Geographic Atrophy Segmentation Using SD-OCT

In a previous article, we talked about Geographic Atrophy segmentation in 2D images. This article focuses on how OCT images shed light on the development

Geographic Atrophy (GA)

Geographic Atrophy (generally called GA) is a case of advanced Dry AMD (Age-related Macular Degeneration) which might lead to vision loss. As a consequence of

Retina Montage Software

RSIP Vision has developed software which finds common points within the images and reorients them to ‘stitch’ together an accurate panoramic presentation of the retina. Our image stitching technology reconstructs the vascular tree of the retina also when images are acquired at different angles. Its end result enables the ophthalmologist to analyze the patient’s retinal vascular tree through an efficient and non-invasive process.

Cataract surgery software

Our technology can guide surgeons performing a cataract surgery procedure, by tracking points of interest and their movement. In this way, cuts will be minimized and all operations will be performed with the highest precision. RSIP Vision is able to do that thanks to sophisticated detection and extraction algorithms in the field of image processing, providing the most accurate cataract surgery tool.

Optical Coherence Tomography Angiography

Optical coherence tomography angiography uses OCT to produce high-resolution images of the vascular tree in the eye. A fast and non-invasive procedure, it generates high resolution tridimensional images. Stitching multiple images together and increasing image information and clarity, RSIP Vision’s solution allows physicians to quickly and accurately detect pathologies related to vascularization without side effects or clinical hazards.

Automatic Pupil Distance Measurement

Modern eye glasses need high precision measurements to ensure the best fit. Interpupillary distance, the distance between the projections of the pupil on the cornea, is one of the most important measurements. Sophisticated algorithms, developed by RSIP Vision to determine with high precision the center of vision corresponding to the pupil, have been integrated into machinery used in eye clinics and embedded as an application in portable devices, such as cell phones.

Multi-modal registration of retina images

Is it possible to perform combination of fundus images coming from different imaging equipment or technologies and taken from different angles? RSIP Vision apparently can, since we used our expertise in computer vision for ophthalmology to provide software to a client who wanted to combine direct images of the fundus with fluorescein images, which need to be reconstructed before being connected together to form a more detailed image. The end result provides ophthalmologists with detailed images of the retina, ensuring more efficient and accurate patient diagnosis.

RSIP Vision at American Academy of Ophthalmology (AAO)

Image processing for ophthalmology at AAO 2016

We were glad to participate in the American Academy of Ophthalmology (AAO) annual meeting that took place at the McCormick Place, Chicago, the largest exhibition

Stabilization in fluorescein angiography

One of the most common tests in ophthalmology is fluorescein angiography: fluorescein is injected in the blood and it moves immediately through the blood vessels

Automatic Lesion Detection in Fundus Images

Diabetic Retinopathy (DR) is an eye disease resulting from long-term diabetic condition. About 80% of long-term diabetic patients suffer from some degree of DR, which

Measurement of Retinal Thickness

Retinal thickness is a key measurement used to assess the health of the retina and whether it needs any treatment. Thickness measures can be compared to optimal ranges or to data from the same patient over time, helping ophthalmologists to identify retinal disorders. Advanced optimization methods, borrowed from graph theory, enable us to solve the complex challenge of measuring retinal thickness within reasonable processing time.

Finding Cysts, Part Five: Final Detection

The goal is to automatically detect the appearance of Cystoid Macular Edema (CME) in Optical Coherence Tomography (OCT) images. The deep learning technique used, Convolutional Neural Networks, takes as an input patches of pixels from within the retina. These patches were generated from previous segmentation of retinal images. A further segmentation of the retina is performed using an image processing algorithm called SLIC. Every superpixel thus generated, after being labeled as in the OCT scan, is fed into the neural network to detect the cyst.

Explaining OCT Scans

What are OCT Scans? Optical coherence tomography (OCT) is a non-invasive imaging method, which produces high-resolution volumetric histological images of tissue. To penetrate deep into biological

Finding Cysts Part Four: Seed Detection

A series of five articles on our Cysts Detection project using deep learning and Convolutional Neural Networks: 1) our cyst detection method; 2) the cyst denoising process; 3) the retinal layer segmentation; 4) the automatical seed-detection; 5) the final detection of the cysts. Our method is exceptionally successful at finding the cysts themselves and most of their area. Remarkable results are achieved even when using relatively small datasets in the training process.

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Tag: Ophthalmology

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