Abstract: A computer-implemented method of machine learning based medical treatment optimization. Embodiments include receiving, by an artificial intelligence (AI) agent, a request related to treating a patient. Embodiments include retrieving medical data that is related to the request from one or more source devices, whereint he medical data includes multiple data modalities. Embodiments include generating, using a multimodal machine learning model, response content related to treating the patient based on the request and the medical data. Embodiments include providing the response content via an output device.

Abstract: The present disclosure relates to the field of image definition recognition, and discloses a logging image definition recognition method and device, medium and electronic equipment. The method comprises: establishing a logging image sample library comprising a plurality of logging images; acquiring actual definition information corresponding to the respective logging images; acquiring a plurality of definitions corresponding to the respective logging images; determining target weights corresponding to the respective target image definition determination algorithms according to the plurality of definitions and the actual definition information corresponding to the respective logging images; and determining a definition of a target logging image by the respective target image definition determination algorithms and the target weights corresponding to the respective target image definition determination algorithms.

Abstract: A system includes an ophthalmic microscope configured to capture video of an ophthalmic treatment. A computer system receives the video and a treatment plan for the ophthalmic treatment and processes the video and the treatment plan using a machine learning model to divide the video into a plurality of video segments, each video segment of the plurality of video segments corresponding to a procedure of a plurality of procedures included in the ophthalmic treatment. The computer system may process the video using a machine learning model to label each frame of a plurality of frames of the video with an identifier of a procedure of a plurality of procedures included in the ophthalmic treatment represented in each frame and at least one of (a) select information for display on the display device according to the identifier and (b) control operation of surgical equipment according to the identifier.

Abstract: Certain embodiments provide a method of performing ophthalmic surgical procedures. The method includes ingesting and preparing pre-operative data and intra-operative data associated with a patient's eye for further processing. In certain embodiments, the method further includes integrating the pre-operative data and intra-operative data to generate context sensitive data for further processing. The method also includes classifying and annotating the pre-operative data, the intra-operative data, and the context sensitive data. The method also includes extracting one or more actionable inferences from the pre-operative data, the intra-operative data, context sensitive data, and the classified and annotated data. The method further includes triggering, based on the one or more actionable inferences, one or more actions on an imaging system or a surgical system.

Abstract: In certain embodiments, a system, a computer-implemented method, and computer-readable medium are disclosed for light efficient fluorescence imaging. The retina is flashed with broadband light and returned light is imaged after passing through one or more filters, such as notch filers, low-pass filters, and high-pass filters. Images may be captured with a single camera or at least two cameras, one capturing transmitted light from the filter and the other capturing returned light. Images may be combined by subtraction and/or addition to obtain a combined image representing light within a passband whereas no passband filters are used during imaging.

Abstract: In certain embodiments, an ophthalmic system and computer-implemented method for analyzing multiple spectral information to generate ophthalmic information are described. In an exemplary ophthalmic system, multiple spectral information associated with an eye of a patient is captured via an imaging system. A first set of information and a second set of information are extracted from the multiple spectral information. A visualization of the multiple spectral information is generated using the first set of information. The first set of information and the second set of information are evaluated using different deep learning models to generate ophthalmic information. The ophthalmic information is sent to a user for diagnostic evaluation.

Abstract: Real-time instrument position estimation and guidance for ophthalmic surgery are described. An ophthalmic surgical system may include a first camera to obtain a first image feed of an ophthalmic surgical procedure and a second camera to obtain a second image feed of the ophthalmic surgical procedure. The ophthalmic surgical system may further include a real-time instrument position estimation module implemented in a non-transitory computer-readable storage medium and configured to determine, in real-time, a relative position of an instrument feature with respect to an anatomical feature of an eye based on the first image feed and the second image feed during the ophthalmic surgical procedure. The real-time instrument position estimation module may be further configured to output, in real-time, a surgical guidance based on the relative position of the instrument feature with respect to the anatomical feature of the eye during the ophthalmic surgical procedure.

Abstract: A system and method for visually enhancing an original image of an eye includes a visualization module. A controller is configured to convert an output of the visualization module to a first pixel cloud in a first color space and map the first pixel cloud to a second pixel cloud in a second color space. The method includes identifying at least one selected zone in the second color space. The controller is configured to move the selected zone from an original location to a modified location in the second color space. The second pixel cloud is updated to obtain a modified second pixel cloud, which is transformed into a third pixel cloud in the first color space. An enhanced image is formed based in part on the modified second pixel cloud and provides selective visual enhancement in the selected zone without affecting contrast in a remainder of the original image.

Abstract: A computer-implemented method of acquiring ophthalmic images for clinical use may include receiving, at a user device including a camera, a command to initiate image acquisition relative to an eye of a patient. The computer-implemented method may also include, responsive to the receiving, interactively guiding, at the user device, a user to capture at least one image of the eye that satisfies one or more clinical image parameters. The computer-implemented method may also include, responsive to the interactively guiding, the user device causing the at least one image to be stored in relation to the patient in a location accessible to an ophthalmic surgical system.

Abstract: In certain embodiments, a system, a computer-implemented method, and computer-readable medium are disclosed for light efficient fluorescence imaging. The retina is flashed with broadband light and returned light is imaged after passing through one or more filters, such as notch filers, low-pass filters, and high-pass filters. Images may be captured with a single camera or at least two cameras, one capturing transmitted light from the filter and the other capturing returned light. Images may be combined by subtraction and/or addition to obtain a combined image representing light within a passband whereas no passband filters are used during imaging.

Abstract: The present application provides a display panel, a method for manufacturing a display panel, and an electronic device. In the display panel having at least an isolation structure, a first encapsulation layer covering a non-active area is fabricated while fabricating a third light-emitting device and its corresponding encapsulation unit, and the encapsulation effect of the display panel can be guaranteed. Furthermore, in the display panel, the method for manufacturing a display panel, and the electronic device provided in the present application, the first encapsulation layer is formed simultaneously with the third encapsulation unit corresponding to the third light-emitting device fabricated last, and it is possible to prevent the etching operation on the light-emitting device and the encapsulation unit fabricated later from affecting the first encapsulation layer in the non-active area, thereby ensuring the encapsulation reliability of the first encapsulation layer.

Abstract: A system and method for visually enhancing an original image of an eye includes a visualization module. A controller is configured to convert an output of the visualization module to a first pixel cloud in a first color space and map the first pixel cloud to a second pixel cloud in a second color space. The method includes identifying at least one selected zone in the second color space. The controller is configured to move the selected zone from an original location to a modified location in the second color space. The second pixel cloud is updated to obtain a modified second pixel cloud, which is transformed into a third pixel cloud in the first color space. An enhanced image is formed based in part on the modified second pixel cloud and provides selective visual enhancement in the selected zone without affecting contrast in a remainder of the original image.

Abstract: Disclosed are devices, systems, and methods for multi-modal, wearable sensors, including an electrochemical-ultrasonic transducer-based sensor, that can simultaneously detect and monitor one or more bio-analyte markers and one or more physiological markers. In some aspects, a wearable, acoustic-electrochemical sensor device includes a flexible substrate, one or more electrochemical sensors disposed on the flexible substrate, a physiological sensor comprising an array of acoustic transducers disposed on the flexible substrate, wherein the sensor device is operable to simultaneously detect and monitor one or more analyte markers and physiological markers including hemodynamic parameters.

Abstract: Certain aspects of the present disclosure provide an ophthalmic imaging device for enhancing images. The device comprises an image capture component configured to generate an image stream comprising a first frame preceding a second frame, both capturing a branch of veins in an eye. The device further comprises an image processor configured to calculate first order statistics for a plurality of blocks for the first frame and to interpolate first order statistics for the first frame based at least in part on the branch of veins. The image processor is also configured to generate a tone mapping function and calculate tone mapping values for individual pixels of the second frame based on the tone mapping function. The image processor is additionally configured to generate an enhanced frame based on the calculated tone mapping values for individual pixels of the second frame to the pixels of the second frame.

Abstract: A system for tracking an ophthalmic surgery. The system includes at least one digital camera configured to generate images of an eye, a memory comprising executable instructions, and an electronic control unit (ECU) in data communication with the memory. The ECU is configured to execute the executable instructions to collect images of an eye with at least a portion of the images being obtained intra-operatively and to create a spatial map of the eye based at least partially on the images of the eye. The ECU is also configured to execute the executable instructions to store at least one parameter regarding a clinical feature of the eye in connection with a spatial registration of clinical feature in the spatial map and recall a location of the clinical feature by tracking a location of the clinical feature in the spatial map.

Abstract: A system includes an ophthalmic microscope including first and second illuminator optics configured to emit light onto an eye of a patient. The system further includes a controller coupled to the first and second illuminator optics. The controller is configured to operate in a first mode in which light emitted by the first illuminator optics and light emitted by the second illuminator optics has a first configuration. The controller is configured to operate in a second mode in which the light emitted by the first illuminator optics and the light emitted by the second illuminator optics are configured to enhance visibility of one or more Purkinje images projected onto the eye of the patient by the first illuminator optics relative to the first configuration. Registration of the optical axis of the eye, robotic alignment, and autofocusing may also be performed using Purkinje images.

Abstract: A system includes an ophthalmic microscope including a camera and a controller coupled to the camera. The controller configured to receive at least one image from the camera, the at least one image including a representation of an eye of a patient. The controller segments the at least one image using a machine learning model to obtain at least one segmented image including one or more labels of one or more Purkinje images represented in the at least one image. The controller produces an output according to the at least one segmented image. The output may be an estimate location of the visual axis of the eye. The output may include an estimate of an offset between the visual axis and a center of an IOL implanted in the eye. The segmented image may further label the IOL and possibly one or more items of anatomy of the eye.

Abstract: Provided herein are methods, devices, and systems that pertain to solid-state sensor and sensor-reading meter for touch-based rapid physiological and chemical sensing.

Abstract: Particular embodiments disclosed herein provide an alignment guide for aligning a toric IOL during surgery. An image with a reference axis is obtained, such as from a digital microscope, and processed, to obtain a segmented image excluding portions of the image outside of a limbus of a patient's eye. The segmented image is processed, such as using an autoencoder, to label alignment marks on the IOL and possibly other features of the IOL. The label is processed, such as using a logistic regression model, to estimate an IOL axis of the IOL intersecting the alignment marks. An output image is generated from the image that has superimposed thereon guides to a surgeon, such as a line representing the IOL axis, a rotation direction indicator, and a number or other representation of a difference between the reference axis and the IOL axis.

Abstract: A method for enhancing a digital image of a patient's eye includes illuminating the patient's eye with light from a modulable lighting source and collecting a digital image of the illuminated eye while the eye is tracked via motion tracking logic of an electronic control unit (ECU). The method includes receiving input signals as a request to enhance an area-of-focus of the eye, automatically identifying the area-of-focus via artificial intelligence (AI) logic in response to the input signals, and selectively adjusting characteristics of the lighting source and constituent pixels of the digital image located outside of the area-of-focus. The method further includes transmitting display control signals to one or more display screens to present an enhanced digital image of the eye. A system for enhancing the digital image includes the lighting source, digital camera, and ECU.