99 results about "Optic disc" patented technology

The present invention relates to the design and implementation of a three stage computer-aided screening system that analyzes fundus images with varying illumination and fields of view, and generates a severity grade for diabetic retinopathy (DR) using machine learning. In the first stage, bright and red regions are extracted from the fundus image. An optic disc has similar structural appearance as bright lesions, and the blood vessel regions have similar pixel intensity properties as the red lesions. Hence, the region corresponding to the optic disc is removed from the bright regions and the regions corresponding to the blood vessels are removed from the red regions. This leads to an image containing bright candidate regions and another image containing red candidate regions. In the second stage, the bright and red candidate regions are subjected to two-step hierarchical classification. In the first step, bright and red lesion regions are separated from non-lesion regions. In the second step, the classified bright lesion regions are further classified as hard exudates or cotton-wool spots, while the classified red lesion regions are further classified as hemorrhages and micro-aneurysms. In the third stage, the numbers of bright and red lesions per image are combined to generate a DR severity grade. Such a system will help in reducing the number of patients requiring manual assessment, and will be critical in prioritizing eye-care delivery measures for patients with highest DR severity.

The invention provides a macula lutea image detection method and equipment. The macula lutea image detection method comprises the steps that a fundus image is acquired; a machine learning model is utilized to recognize the fundus image to output the fundus image obtained after feature regions are marked, wherein the feature regions are at least one of a macula lutea region, an optic disc region and a macula lutea and optic disc united region, and the machine learning model is obtained by performing training through sample images at the positions of the known feature regions; and according to the fundus image obtained after the feature regions are marked, the fundus image obtained after a macula lutea image position is marked is output.

The invention discloses a fundus image registering method based on SIFT characteristics. The method comprises: conducting angle classification to a batch of inputted fundus images; calculating the transformative relationship among the images; converting the images onto the same background; and through the rapid switching of the images, finding out which parts of the fundus change. The invention mainly uses a fuzzy convergence optic disc positioning algorithm and conducts angle classification to the batch of inputted fundus images according to the position of the optic disc wherein the angle classification is referred as two types: the left side and the right side; and then in each image classification, a selected and uploaded first image is used as a reference for other images to register with; the SIFT characteristic points of all the images are extracted and the matching relation between every two points is calculated. Finally, the RANSAC algorithm is used to calculate the transformation model parameters between every two images. The images are converted onto the same background according to the transformation model; and an image switching interval is configured so that through the switching of the images, it is possible to find out the change among the images rapidly and accurately.

The invention provides an automatic retinal blood vessel segmentation method for clinical diagnosis of glaucoma. Through the method, the influence of bright regions such as optic disc and exudate is eliminated by fusing five models depending on different image processing technologies, namely a matched filter, a neural network, multi-scale line detection, scale space analysis and morphology. At thesame time, massive data is not needed to establish a retinal blood vessel segmentation model, so the method greatly reduces the amount and complexity of data to be processed, is easy to realize, andcan effectively improve the efficiency of retinal blood vessel segmentation. The method also utilizes the region growth method and the gradient information to carry out iterative growth on the background and the blood vessel region on the basis of a multimodal fusion result, the segmentation results exhibit better continuity and smoothness, more retinal vascular details and more complete retinal vascular network can be kept, and thus the method effectively assists ophthalmologists in diagnosing diseases and lightens the burden of ophthalmologists.

The invention discloses a quick optic disc positioning method based on multi-scale macula detection. The quick optic disc positioning method includes the steps of 1, masking fundus images; 2, performing boundary filling to the fundus images; 3, determining candidate regions of optic discs; 4, excluding boundary candidate positions; and 5, determining positions of the real optic discs. As the optic discs are represented by bright-yellow circular regions of different sizes, multiple candidate regions of optic discs are determined according to the multi-scale space theory and the LOG macula detection technology, and then the real optic discs are positioned on the basis of appearance characteristics of the candidate regions and local vasculature characteristics. By the quick optic disc positioning method, optic disc positioning is performed on the fundus images after the fundus image are reduced, and the real-time detection effect is achieved; due to the multi-scale detection capacity, the method is adaptable to different size of image data sets, and has the advantages easiness, high accuracy, quick positioning and the like.

The invention provides a left and right eye recognition method based on eye ground image features, and belongs to the field of medical digital image processing. The method comprises the steps of firstly, processing the acquired eye ground image, then acquiring corresponding information from the processed image via three different methods according to different features of optic discs and blood vessels respectively, finally setting corresponding variables for the three methods and judging whether the methods can be used for judging left and right eyes, performing left and right eye recognition on the combination of the eye ground image according to the recognition result obtained by each method and outputting the recognition result.. The method can be used for quickly and accurately recognizing that the given eye ground image belongs to the left eye or the right eye, is high in recognition accuracy, simple and easy to operate, and has high application value.

The invention discloses a method for fine segmentation of the eye ground optic disc based on SLIC super-pixel segmentation. The steps are as follows: super-pixel segmentation, vascular segmentation based on morphological processing and R-G double-channel color threshold segmentation are carried out on an input eye ground image, and after expansion of a connected region obtained from color threshold segmentation, a corresponding Toeplitz matrix template is selected according to the pixel coordinates of the connected region to filter an eye ground vascular image to obtain the center position ofthe optic disc; and then, a candidate area of the optic disc is extracted and the internal blood vessels are removed, threshold segmentation is carried out on the candidate area of the optic disc through a binarization method, the ROI (Region of Interest) of the optic disc ellipse is determined by using an ellipse fitting method based on least squares, super pixels with a certain overlapping areaare retained according to the SLIC super-pixel segmentation result, and thus, fine segmentation of the optic disc is completed. Through the method, automatic positioning and fine segmentation of the optic disc are realized, better contour information of the optic disc can be retained, less time is consumed, other follow-up processing of the eye ground image is facilitated, and assistant diagnosiscan be provided for ophthalmologists.

The invention relates to a glaucoma early stage screening method using a computer to carry out automatic analysis for eyeground photographs, thus fast calculating an eye cup-eye disk C/D ratio value in real time; the features are that the C/D value is compared with a set glaucoma risk value so as to determine the glaucoma existence possibility. The advantages are that the cup/disk ratio changes formed by glaucoma pathology optic nerve progressive damages are employed, thus carrying out automatic eyeground photograph reading analysis under computer assistance. Image fuzzy processing, OTSU algorithm and computer operation are introduced so as to greatly improve determination result accuracy and instantaneity when compared with a conventional diagnosis method singly using an eyeground photograph reading mode, and avoiding expensive and complex detection equipment; low cost high efficiency screening method can be carried out so as to realize glaucoma early discovery and early diagnosis; a database is built, and a screening and uploading step by step mode is employed, thus gradually improving a big data development system under a three-level networking system.

The invention discloses an optic disc positioning method for a retina image. The optic disc positioning method for the retina image comprises the following steps that (a) bright plaques in the background are erased, and meanwhile blood vessel features are reserved; (b) candidate positions of the center of the optic disc are determined based on blood vessel convergence tendency features; (c) the finial position of the center of the optic disc is determined from the candidate positions of the center of the optic disc based on blood vessel direction features. The optic disc positioning method for the retina image can solve the problem that the positioning of the optic disc is prone to interference brought by various lesions and other noise in the background, and the accuracy and the speed of the positioning of the optic disc under the complex background can be improved.

The invention relates to the technical field of image processing, in particular to a diabetic retina image quality detection method based on an image analysis technology. The method comprises the following steps of: preprocessing the fundus image, performing morphological treatment, equalization treatment and filtering treatment on the fundus image during the pretreatment process, performing brightness detection, optic disc detection and definition detection after the pretreatment, and finally obtaining the fundus image to be diagnosed, and diagnosing diabetic retinopathy. The preprocessing operation in the method greatly improves the visibility of the retinal fundus image, It is more advantageous for doctors to diagnose and analyze the patients' condition, and the quality inspection operation can greatly reduce the occurrence of the unqualified fundus images taken at the census spots. The fundus images which pass the quality inspection can be used for the preliminary diagnosis of diabetic retinopathy.

The invention provides a method for detecting the rigid exudate lesion in a fundus image based on a convolution neural network. The method comprises the following steps of 1) preprocessing the fundusimage and enhancing image contrast through Gamma correction algorithm; 2) carrying out block processing on that image to expand the data; 3) using the lesion results manually annotated by experts in DRIVE, MESSIDOR database as the monitoring data, using the adjusted VGG-16 network to train the block image and introducing the channel weighting module to establish the dependency of the feature channel explicitly by learning; 4) using the trained network model to detect the hard exudate lesion in the fundus image. Compared with the traditional scheme, the method of the invention avoids the complicated image processing process, is not affected by the fundus optic disc and cotton floc spots on the hard exudate lesion, realizes the high-precision detection of the hard exudate lesion, and can bewidely used in the field of automatic screening of the fundus rigid exudate.

A method for detecting disc haemorrhages in a retinal fundus image. The method includes (a) identifying a ring-shaped region of interest in the retinal fundus image encompassing the optic disc boundary; (b) removing blood vessel regions in the identified region of interest; (c) detecting candidate disc haemorrhages from the removed blood vessels regions in the identified region of interest; and (d) screening the candidate disc haemorrhages. The detected disc haemorrhages may be used to aid in the detection of glaucoma.

The invention discloses a retina image analysis method applied to calculation equipment. The method comprises steps that a to-be-analyzed retina image is acquired, and the to-be-analyzed retina image is pre-processed to acquire an enhanced image; the enhanced image is filtered to extract a background image; a bright region image and a dark region image are determined according to RGB color values of pixels of the enhanced image and the background image; a videodisc region and a bright noise region are determined, and the videodisc region and the bright noise region are removed from the bright region image to acquire an exudation region; a blood vessel region and a dark noise region are determined, and the blood vessel region and the dark noise region are removed from the dark region image to acquire a hemorrhage region. The invention further discloses a retina image analysis device of the retina image analysis method, and the calculation equipment equipped with the retina image analysis device. The method is advantaged in that the exudation region and the hemorrhage region of the retina image can be rapidly acquired through segmentation.

The invention discloses an optimal sibling similarity-based fundus image optic disc positioning method and a system thereof. The method comprises the following steps: (1) selecting a healthy fundus image, and extracting an image in a minimum circumscribed rectangle as a template image, wherein the minimum circumscribed rectangle is in the healthy fundus image and contains an optic disc region; (2)preprocessing the template image and a to-be-matched image; (3) calculating an optimal sibling similarity between the template image and the to-be-matched image; (4) searching in the to-be-matched image, and determining a region corresponding to the maximum value of the optimal sibling similarity as a final positioning result. According to the invention, a new concept is provided for the positioning work of the fundus image optic disc, and a good effect is achieved.

A method of assessing the quality of an retinal image (such as a fundus image) includes selecting at least one region of interest within a retinal image corresponding to a particular structure of the eye (e.g. the optic disc or the macula), and a quality score is calculated in respect of the, or each, region-of-interest. Each region of interest is typically one associated with pathology, as the optic disc and the macula are. Optionally, a quality score may be calculated also in respect of the eye as a whole (i.e. over the entire image, if the entire image corresponds to the retina).

A method for determining the position of an optic cup boundary in a 2D retinal image. The method includes detecting kinks in blood vessels at an estimated boundary of the optic cup and the optic disc, and determining the position of the optic cup boundary in the 2D retinal image based on the detected kinks. The determined optic cup boundary may be used for determining a CDR which may in turn be used for determining a risk of contracting glaucomatous.

The invention discloses a flexible cable for a retinal prosthesis. The flexible cable comprises a microelectrode with two mounting holes corresponding to two sides of the optic disc during implantingof the retina, wherein the microelectrode comprises an electrode area located between the two mounting holes and an elastic portion connected to the electrode area, the elastic portion is deformable and stretchable at least in a longitudinal direction of a connection line of the two mounting holes, and the electrode area is provided with a plurality of stimulation electrodes; a leading portion connected with an electronic device; a connection portion connected between the microelectrode and the leading portion and including a plurality of wires respectively connected to the plurality of stimulation electrodes. The flexible cable enables the microelectrode to be uniformly stressed and better attached to the retina to obtain a more effective stimulating effect. The invention also discloses an implanting device for the retina and the retinal prosthesis.

The present invention relates to the technical field of computers and particularly relates to a method for rapidly segmenting a fundus optic disc based on multiple circles. The method comprises a stepof (1) determining a disc center based on high brightness and blood vessel characteristics including the steps of (1.1) color retinal image threshold segmentation, (1.2) candidate center marking and(1.3) positioning to a disc center, and a step of (2) the segmentation of the optic disc based on a multi-circle minimum convex hull operation including the steps of (2.1) morphological removal of blood vessels by using an expansion operation, (2.2) Hough circle transformation, and the segmentation of an optic disc area after the expansion of the optic disc by using canny operator double thresholds to obtain a binarized edge image E, and (2.3) a multi-circle minimum convex hull operation. The method for segmenting the optic disc by the multiple circles is used, the convex hull operation is carried out on a plurality of circles detected inside the optic disc, and the speed and precision of the segmentation can be effectively improved.

The invention provides an eyeground picture processing method based on a neural network, comprising the following steps: S1, acquiring a plurality of eyeground pictures through shooting by a camera; S2, detecting an area including an optic disc and an optic cup in the fundus picture, and cutting the area including the optic disc and the optic cup from the fundus picture to obtain an initial samplepicture; 3, circling an optic disc region and an optic cup region on the initial sample picture and filling the optic disc region and the optic cup region with different color respectively to obtaina training sample picture; S4, constructing a neural network; 5, training the neural network through a plurality of pictures of the train samples, and determining the parameters of the neural network;this method can help doctors and nurses to judge the cup-to-dish ratio of fundus picture efficiently and accurately, and improve the efficiency and accuracy of glaucoma diagnosis.

Disclosed is a method for measuring the retinal blood vessel diameter and thickness of a vessel wall. The method is characterized by including: adopting an SD-OCT (spectral domain optical coherence tomography) scanning system for measurement and selecting all the retinal blood vessels in an area with the distance apart from the edge of an optical disc 0.5-1.0 times of the diameter of the optical disc as measuring objects through the SD-OCT system; allowing a scanning line to be perpendicular to the running direction of a positioning blood vessel to acquire a cross section figure of the retinal blood vessels; magnifying the scanned cross section figure of the blood vessels; moving a scale ruler to measure inner diameter and outer diameter of each blood vessel, wherein the thickness of the vessel wall=(the outer diameter-the inner diameter)/2; calculating the central retinal artery equivalent Wt; taking the central retinal artery equivalent Wt=(0.87Wa<2>+1.01Wb<2>-0.22WaWb-10.73)<1/2> as a diagnostic basis. The method has the advantages of being free of damage, non-invasive, free of mydriasis and high in measurement precision.