Verily Life Sciences LLC

Chinmay Belthangady

Seung Ah Lee

Eden Rephaeli

Daniele Paolo Piponi

Supriyo Sinha

John D Perreault

Tamara Troy

Sam Kavusi

Eliezer Glik

Ryan Kramer

Cheng-Hsun Wu

Faisal Mahmood Kashif

James Michael Higbie

Maximilian Kapczynski

Brian M Rabkin

Suresh Alla

Charles Santori

James Polans

The technology described herein is directed to a fundus camera and, more specifically, to a fundus camera having a display that projects active visual alignment stimuli onto an eye of an examinee via one or more components of an optimal assembly. The active visual alignment stimuli are dynamically adjusted to guide an examinee toward optical alignment for fundus imaging.

Active visual alignment stimuli in fundus photography

Systems, apparatuses, and methods for detecting carious lesions are described herein. In an example, the systems in an optical interrogator including a single-pixel photodetector responsive to short-wave infrared light and operatively coupled to a controller. In an example the optical interrogator includes a light engine for emitting light, a scanning mirror assembly and a single-pixel photodetector. In an example, the methods include causing the light engine to emit light having wavelengths in a range of about 900 nm to about 1,700 nm; selectively directing the light over different portions of a tooth with a scanning mirror assembly to provide scattered light; and correlating scattered light signals generated by the single-pixel photodetector in response to the scattered light with the portion of the tooth.

Systems for detecting carious lesions in teeth using short-wave infrared light

Embodiments may include a method to estimate motion data based on test image data sets. The method may include receiving a training data set comprising a plurality of training data elements. Each element may include an image data set and a motion data set. The method may include training a machine learning model using the training data set, resulting in identifying one or more parameters of a function in the machine learning model based on correspondences between the image data sets and the motion data sets. The method may further include receiving a test image data set. The test image data set may include intensities of pixels in a deep-tissue image. The method may include using the trained machine learning model and the test image data set to generate output data for the test image data set. The output data may characterize motion represented in the test image data set.

Speckle contrast analysis using machine learning for visualizing flow

The present disclosure relates to systems and methods for cellular imaging and identification through the use of a light sheet flow cytometer. In one implementation, a light sheet flow cytometer may include a light source configured to emit light having one or more wavelengths, at least one optical element configured to form a light sheet from the emitted light, a microfluidic channel configured to hold a sample, and an imaging device. The imaging device may be adapted to forming 3-D images of the sample such that identification tags attached to the sample are visible.

Light sheet imaging flow cytometer

Systems and methods for acquiring images of a sample are provided. According to an aspect of the invention, a system includes a first light source that emits first light having a first wavelength as a temporally continuous beam; a second light source that emits second light having a second wavelength as a temporally modulated beam; and a scanning mirror that raster scans the first light across a sample during a raster scan period, and projects a structured light pattern of the second light onto the sample during the raster scan period. A first image of the sample is generated from at least a portion of the first light that is backscattered from the sample during the raster scan period, and a second image of the sample is generated from at least a portion of the second light that is backscattered from the sample during the raster scan period.

Short-wave infrared and 3D topographic imager

Systems, apparatuses, and methods for detecting carious lesions are described herein. In an example, the systems in an optical interrogator including a single-pixel photodetector responsive to short-wave infrared light and operatively coupled to a controller. In an example the optical interrogator includes a plurality of lasers for emitting laser light, a scanning mirror assembly and a single-pixel photodetector. In an example, the methods include causing the plurality of lasers to emit the laser light having wavelengths in a range of about 900 nm to about 1,700 nm; selectively directing the laser light over different portions of a tooth with a scanning mirror assembly to provide scattered light; and correlating scattered light signals generated by the single-pixel photodetector in response to the scattered light with the portion of the tooth.

A fundus camera and method of operating the fundus camera are described. The fundus camera includes an image sensor, an eyepiece lens, an illumination source, and an alignment target. The image sensor captures image light of a retina within an eye. The eyepiece lens is disposed to pass the image light of the retina to the image sensor. The illumination source is disposed to direct illumination light onto the retina through the eyepiece lens. The illumination source is further disposed around a first aperture through which the image light of the retina passes from the eyepiece lens to the image sensor. The alignment target is coupled to output an alignment image through the eyepiece lens to the eye and disposed around a second aperture through which the image light of the retina is passed to the image sensor and the illumination light is passed to the eyepiece lens.

Non-mydriatic self-imaging fundus camera

A device and a method to measure the concentrations of oxygenated and deoxygenated hemoglobin in tissue around a tumor via near-infrared (NIR) spectroscopy with a photonic mixer device (PMD) is described.

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San Francisco, CA, United States of America

Chinmay Belthangady