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150 results about "Ophthalmoscopes" patented technology

Devices for examining the interior of the eye, permitting the clear visualization of the structures of the eye at any depth. (UMDNS, 1999)

Ophthalmology oct system and ophthalmology imaging method

The embodiment of the invention discloses an ophthalmology OCT system, comprising a posterior segment intraocular OCT imaging system and an anterior eye segment OCT imaging system. The posterior segment intraocular OCT imaging system comprises a light path conversion device, the anterior eye segment OCT imaging system comprises an anterior eye segment probe imaging device comprising an ophthalmoscope, a first dichroscope and a first lens; wherein, when the ophthalmology OCT system carries out an anterior eye segment scanning imaging, and after the light path conversion device receives a light path conversion instruction, signal light passing through a collimating mirror and a scanning device respectively are converted to the anterior eye segment probe imaging device; the anterior eye segment probe imaging device drives the first dichroscope to reflect the signal light to the ophthalmoscope to carry out the anterior eye segment scanning imaging. Correspondingly, the invention also discloses an ophthalmology OCT imaging method. By employing the invention, when the anterior eye segment imaging is carried out on human eye, fixation points can always be kept clear via refractive compensation, and the anterior eye segment probe imaging quality is not affected.
Owner:SHENZHEN CERTAINN TECH CO LTD +1

Line-scanning confocal ophthalmoscope system based on laser diffraction and method

The invention relates to a line-scanning confocal ophthalmoscope system based on laser diffraction and a method. The system comprises a linear beam generation module, a beam-splitting module, a scanning module, an imaging module and an output module. The invention is characterized in that: the intensity of the linear beam generated by the line-scanning confocal ophthalmoscope system is uniformly distributed in a non-Gaussian form, a scanning galvanometer is adopted to scan the linear beam in a one-dimensional space to illuminate an ocular fundus retina, meanwhile, a linear detector is used for imaging the non-scanning linear beam reflected by the ocular fundus retina, and since the system only uses one scanning galvanometer and one linear detector, the number of the moving parts is less; meanwhile, a confocal slit is conjugated with the ocular fundus retina plane, consequently, the affection of the stay light of the non-retina plane on the imaging quality is eliminated, and thereby the high resolution of the confocal imaging principle. The system has the advantages of good linear beam quality, simple system structure, easy manufacturing, short light path, easy adjustment, small size, applicability, high stability and high imaging frame frequency.
Owner:INST OF OPTICS & ELECTRONICS - CHINESE ACAD OF SCI

Diabetic retinopathy grade classification method based on deep learning

The invention provides a diabetic retinopathy grade classification method based on deep learning. The diabetic retinopathy grade classification method comprises the steps of: constructing a sample library; removing backgrounds and noise of ophthalmoscope photographs in the sample library; normalizing the images of different brightness and different intensity to the same range by adopting a local mean value subtracting method; adopting random stretching and rotating methods for different samples for data augmentation, and constructing a training set and a test set; training an initial deep learning network model by establishing an input portion architecture, a multi-branch feature transformation portion architecture and an output portion architecture separately; and inputting samples to betested into the trained initial deep learning network model for diabetic retinopathy grade classification. Compared with the traditional processing method, the diabetic retinopathy grade classification method gets rid of the dependence on prior knowledge, and has good generalization ability; and by adopting the designed multiple grades, a small-sized convolution kernel can be used for extracting very tiny lesion features, thereby making the classification results more reliable.
Owner:NORTHEASTERN UNIV

Method and device for fundus oculi affection early diagnosis using time discrimination autofluorescence lifetime imaging

The invention relates to a novel measurement method and the device thereof, which combines the time-resolved self-fluorescence lifetime imaging technology and a laser scanning confocal ophthalmoscopeand realizes the early diagnosis of the ocular fundus diseases by obtaining and analyzing the self-fluorescence intensity and the service life information of the ocular fundus. The light which is emitted by a pulse laser is sent to the scanning head of the laser scanning confocal ophthalmoscope to excite the ocular fundus inner-source flgorgen, and the fluorescence which is emitted from the ocularfundus is collected by a time-correlated single photon counter or a high-repetition-rate synchronous scanning camera, so as to realize the service life measurement and the imaging of the self-fluorescence. As the service life of the self-fluorescence of the ocular fundus is very sensitive to the micro-environment and the cell metabolism state of flgorgen molecule and is not affected by the difference of the intensity of the flgorgen of the ocular fundus, the measurement of the fluorescence service life provides a brand new route for the detection of ocular fundus diseases and the obtainment of the function information of ocular fundus. The invention can become the solution and the basis of the early diagnosis of various ocular fundus diseases, which plays an important role in pathogeny research, clinical diagnosis, staging and typing, prognosis judgement, real-time observation and the analysis of the development of ocular fundus diseases, therefore the invention can be widely appliedin the field of medical research and clinical medical diagnosis.
Owner:SHENZHEN UNIV
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