A medical diagnostic system can assess quality of a representation of a body part determined based on a response of the body part to exposure to electromagnetic waves, process the representation with a disease detection machine learning model to determine a certainty measure for a presence of a disease, determine a quality score for the representation based on the quality of the representation and the certainty measure, and discard the at least one representation based on the quality score. Combining machine learning in conjunction with one another, such as, for quality assessment and disease detection, can provide for more accurate image quality analysis, lead to faster medical imaging, and reduce the need to retake images or entirely re-perform medical imaging. The system can be easier to use, be more robust and faster than other systems by reducing the need to retake images while maintaining performance of the system.

Disclosed techniques evaluate the visual field of a patient's eye using deep learning techniques. A computer system obtains a plurality of cross-sectional scan images of a retina captured by an optical coherence tomography (OCT) device. The retina has an inner retinal layer. A retinal optical texture analysis (ROTA) map of the inner retinal layer is generated from the plurality of cross-sectional scan images. The ROTA map includes a plurality of pixels, and each pixel of the ROTA map corresponds to a respective optical texture signature value S providing information about tissue composition and optical density of the inner retinal layer at a respective retinal location. The computer system applies a machine learning model to process the ROTA map of the inner retinal layer to determine visual field sensitivity of the retina.

A slit-lamp microscope includes a base plate defining an x-axis and a z-axis. The microscope includes a movable base member slidably disposed on the base plate. The microscope includes a computer that generates first and second control signals to induce first and second movement devices, respectively, to move the movable base member in response to a first x-axis command and a first z-axis command, respectively, in first and second remote control messages, respectively. The computer generates a third control signal to induce the digital camera of the microscope assembly to generate a digital image from the light received from the subjects eye in response to the photograph command in a third remote control message.

A system for visualizing a three-dimensional target area of an object with a measuring device which determines a distance of a surgical instrument in a target area with respect to a predetermined structure in the target area, a display unit for representing the views, and a control unit. The control unit controls the display unit such that the display unit is in a first display mode when a determined distance is greater than a predetermined first limit value, and switches from the first display mode into a second display mode when the determined distance changes from being greater than a predetermined second limit value, which is smaller than or equal to the predetermined first limit value, to smaller than the predetermined second limit value.

An apparatus and method for determining at least one visual refraction feature of a subject by showing a visual stimulus to the subject. The apparatus includes an optical system arranged on an optical path between an eye of the subject and the visual stimulus, the optical system being adapted to provide an optical power that is continuously variable as a function of time (t), a control unit for driving the optical power of the optical system and an input device adapted for recording a response of the subject relative to a sharpness of the visual stimulus seen through the optical system, the control unit being adapted to adjust a speed of variation of the optical power (S) as a function of the response recorded.

In an ophthalmologic apparatus, including: an objective lens that faces a subject's eye; an illumination optical system that irradiates a cornea of the subject's eye with illumination light through the objective lens; and a corneal measurement optical system including an interference image capturing camera that takes an image of a corneal reflection light, which is a reflection of the illumination light reflected from the cornea, through the objective lens, a numerical aperture G of the illumination optical system is larger than a numerical aperture g of the corneal measurement optical system.

A method for enhancing digital images during a microsurgery, e.g., an eye surgery, includes collecting digital images of target anatomy using a digital camera as the target anatomy is illuminated by warm white light. The method includes identifying, via a processor in communication with the digital camera, a predetermined stage of the microsurgery. Within the images, the processor digitally isolates a first pixel region, e.g., a pupil pixel region, from a second pixel region, e.g., an iris pixel region, and adjusts a characteristic of constituent pixels thereof. The method, possibly recorded as instructions in a computer-readable medium, may be used to enhance a red reflex at predetermined stages of an eye surgery. A system includes a lighting source for emitting warm white light having a color temperature of less than about 4000° K, the camera, and the processor.

An intraocular pressure (IOP) measurement system. An optical pressure sensor is implantable in the cornea of an eye, wherein the sensor has a sealed cavity that changes shape as a function of IOP of the eye. An optical transmitter that is outside of the eye emits an incident optical beam. A receiver that is also outside of the eye produces an output signal in response to receiving reflections of the incident beam from the sensor. A processor is configured to estimate the IOP of the eye based on processing the output signal of the receiver. Other aspects are also described and claimed.

An optotype calibration method is disclosed. The optotype calibration method includes steps of: (a) when a first optotype and a second optotype located outside an observable area, moving the observable area from an original position until the first optotype or the second optotype appears in the observable area; (b) adjusting a focus mechanism to make the first optotype and the second optotype close to each other; (c) moving the observable area back to the original position; and (d) repeating the steps (a)-(c) until the first optotype and the second optotype align with each other.

Systems and methods are provided for performing optical coherence tomography angiography for the rapid generation of en face images. According to one example embodiment, differential interferograms obtained using a spectral domain or swept source optical coherence tomography system are convolved with a Gabor filter, where the Gabor filter is computed according to an estimated surface depth of the tissue surface. The Gabor-convolved differential interferogram is processed to produce an en face image, without requiring the performing of a fast Fourier transform and k-space resampling. In another example embodiment, two interferograms are separately convolved with a Gabor filter, and the amplitudes of the Gabor-convolved interferograms are subtracted to generate a differential Gabor-convolved interferogram amplitude frame, which is then further processed to generate an en face image in the absence of performing a fast Fourier transform and k-space resampling. The example OCTA methods disclosed herein are shown to achieve faster data processing speeds compared to conventional OCTA algorithms.