The present disclosure provides systems and methods for diagnosing disease. In some aspects, an imaging system is provided that includes a light source configured to illuminate a retina of the eye with light, one or more imaging devices configured to receive light returned from the retina to generate one or more spatial-spectral images of the retina, and a computing device configured to receive the one or more spatial-spectral images of the retina, evaluate the one or more spatial-spectral images, and identify one or more biomarkers indicative of a neurogenerative pathology.

A method and device for multimodal imaging of dermal and mucosal lesions. The method includes using at least two imaging modalities from which one is a 3D scan of the lesion, and, additionally providing information on the distance and angulation between scanning device and the dermis or mucosa and mapping at least the second modality over the 3D data.

Machine learning systems and methods are disclosed for prediction of wound healing, such as for diabetic foot ulcers or other wounds, and for assessment implementations such as segmentation of images into wound regions and non-wound regions. Systems for assessing or predicting wound healing can include a light detection element configured to collect light of at least a first wavelength reflected from a tissue region including a wound, and one or more processors configured to generate an image based on a signal from the light detection element having pixels depicting the tissue region, determine reflectance intensity values for at least a subset of the pixels, determine one or more quantitative features of the subset of the plurality of pixels based on the reflectance intensity values, and generate a predicted or assessed healing parameter associated with the wound over a predetermined time interval.

Apparatus and methods for spectral analysis of a sample are described, for example for carrying out Raman or other optical or spectroscopic analysis of samples such as pharmaceutical dosage forms, including oral solid dosage forms such as tablets or capsules. Such apparatus may comprise delivery optics arranged to direct probe light to a delivery region of the sample, collection optics arranged to collect probe light scattered from a collection region of the sample, and a spectrometer having an entrance port, the spectrometer being arranged to receive the collected probe light from the collection optics at the entrance port of the spectrometer, and to detect spectral features in the received probe light. In particular, the collection optics may comprise Koehler integration optics arranged to process the collected probe light such that the collected light from each point of the collection region is distributed across the entrance port of the spectrometer.

A device for characterizing particles of exhaled air. The device comprises an inlet line directed towards an outer environment with a filter for filtering particles. The inlet line is fluidly connected to a breathing line which comprises an interface through which air is breathable. A measurement line is fluidly connected to the breathing line and is fluidly connected to a particle measurement device for determining a parameter corresponding to the particles of the exhaled air. An inventive method comprises the following steps: Directing ex- haled air to a particle measurement device and determining a parameter corresponding to the particles of exhaled air, the parameter being at least one of the following parameters: Particle number, particle concentration (density), particle diameter, particle mass, particle size distribution, particle mass distribution, particle mass concentration, particle number concentration.

Modulation-encoded light, using different spectral bin coded light components, can illuminate a stationary or moving (relative) target object or scene. Response signal processing can use information about the respective different time-varying modulation functions, to decode to recover information about a respective response parameter affected by the target object or scene. Electrical or optical modulation encoding can be used. LED-based spectroscopic analysis of a composition of a target (e.g., SpO2, glucose, etc.) can be performed; such can optionally include decoding of encoded optical modulation functions. Baffles or apertures or optics can be used, such as to constrain light provided by particular LEDs. Coded light illumination can be used with a focal plane array light imager receiving response light for inspecting a moving semiconductor or other target. Encoding can use orthogonal functions, such as an RGB illumination sequence, or a sequence of combinations of spectrally contiguous or non-contiguous colors.

A venous positioning projector includes an infrared light source module, a light splitting element, an infrared light image capture module, a processor, and a visible light projection module. The infrared light source module outputs a first infrared light to a target surface. The infrared light image capture module includes a filter and an infrared light image capture element. The light splitting element transmits a second infrared light reflected by the target surface to the filter. The infrared light image capture element receives the second infrared light passing through the filter. The processor generates venous image data according to the first infrared light and the second infrared light received by the infrared light image capture element. The visible light projection module generates a visible light based on the venous image data. The visible light is transmitted to the target surface through the light splitting element to generate a venous image.

Method and apparatus can be provided according to an exemplary embodiment of the present disclosure. For example, with at least one first section of an optical enclosure, it is possible to provide at least one first electro-magnetic radiation. In addition, with at least one second section provided within the enclosure, it is possible to cause, upon impact by the first radiation, a redirection of the first radiation to become at least one second radiation. Further, with at least one third section of the optical enclosure, it is possible to cause at least one second radiation to be provided to a tissue. For example, the redirection of the first radiation causes, at least approximately, a uniform optical illumination on of a surface of the tissue.

A system for optical spectroscopy through a probe implanted in a tissue is provided. The system includes a light collecting probe comprising a waveguide formed by a single optical fiber and having a proximal end and a distal end, the proximal end being formed with a taper along which at least one optical window is positioned, wherein light entering at an axial section of the taper generates a specific subset of guided modes defined by the diameter of the single optical fiber at the axial section, the guided modes propagating toward the distal end of the waveguide and generating an output at the distal end of the waveguide; a demultiplexer configured to receive outputs provided by the light collecting probe and discriminate the outputs based on their modal content of origin; and a detector configured to detect the discriminated outputs.

An apparatus, system and process for identifying one or more different tissue types are described. The method may include applying a configuration to one or more programmable light sources of an imaging system, where the configuration is obtained from a machine learning model trained to distinguish between the one or more different tissue types captured in image data. The method may also include illuminating a scene with the configured one or more programmable light sources, and capturing image data that includes one or more types of tissue depicted in the image data. Furthermore, the method may include analyzing color information in the captured image data with the machine learning model to identify at least one of the one or more different tissue types in the image data, and rendering a visualization of the scene from the captured image data that visually differentiates tissue types in the visualization.