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Retinoscopy

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Retinal vessel segmentation using multi-scale textons derived from keypoints.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
This paper presents a retinal vessel segmentation algorithm which uses a texton dictionary to classify vessel/non-vessel pixels. However, in contrast to previous work where filter parameters are learnt from manually labelled image pixels our filter p...

Detecting central fixation by means of artificial neural networks in a pediatric vision screener using retinal birefringence scanning.

Biomedical engineering online
BACKGROUND: Reliable detection of central fixation and eye alignment is essential in the diagnosis of amblyopia ("lazy eye"), which can lead to blindness. Our lab has developed and reported earlier a pediatric vision screener that performs scanning o...

SERR-U-Net: Squeeze-and-Excitation Residual and Recurrent Block-Based U-Net for Automatic Vessel Segmentation in Retinal Image.

Computational and mathematical methods in medicine
METHODS: A new SERR-U-Net framework for retinal vessel segmentation is proposed, which leverages technologies including Squeeze-and-Excitation (SE), residual module, and recurrent block. First, the convolution layers of encoder and decoder are modifi...

Identification of ocular refraction based on deep learning algorithm as a novel retinoscopy method.

Biomedical engineering online
BACKGROUND: The evaluation of refraction is indispensable in ophthalmic clinics, generally requiring a refractor or retinoscopy under cycloplegia. Retinal fundus photographs (RFPs) supply a wealth of information related to the human eye and might pro...