Subpixel line scanning. A slide scanning device comprises a plurality of line sensors (112a, 112b, 112c), each comprising a plurality of pixel sensors. Each line sensor is offset from an adjacent line sensor by a fraction of a length of each pixel sensor, and generates a line image of the same field of view at its respective offset. For each of a plurality of positions on a sample, a processor combines the line images of the same field of view, generated by the plurality of line sensors at their respective offsets, to produce a plurality of subpixels for each of at least a subset of pixels within the line images of the same field of view, and generates an up-sampled line image of the position comprising the plurality of subpixels. Then, the processor combines the up-sampled line images of each of the plurality of positions on the sample into an image.

Apparatus and methods for measuring infrared absorption of a sample that includes delivering a pulse of infrared radiation to a region of the sample, delivering pulses of radiation of a shorter wavelength than infrared radiation to a sub-region within the region, and using one or more properties of the induced photoacoustic signals to create a signal indicative of infrared absorption of the sub-region of the sample.

A mobile phone-based miniature microscopic image acquisition device, and image stitching and recognition methods are provided. The acquisition device comprises a support, wherein a mobile phone fixing table is provided on the support. A microscope head is provided below a camera of a mobile phone. A slide holder is provided below the microscope head, and an lighting source is provided below the slide holder. A scanning movement is performed between the slide holder and the microscope head along X and Y axes, so that images of a slide are acquired into the mobile phone. The slide sample images acquired into the mobile phone can be stitched and recognized, and can be uploaded to the cloud to be processed by cloud AI, thereby significantly improving the accuracy and efficiency of cell recognition, greatly reducing the medical cost, and ensuring more remote medical institutions can apply such technology for diagnosis.

An optical apparatus having an illumination module with a carrier, which has at least one light-transmissive region, for example. The illumination module has a plurality of light sources, which are arranged on the carrier.

A common beam scanning retinal imaging system comprises: a light source module (1), an adaptive optics module (2), a beam scanning module (3), a small field-of-view relay module (5), a large field-of-view relay module (6), a sight beacon module (9), a pupil monitoring module (7), a detection module (8), a control module (10) and an output module (11). The system can perform real-time correction of human eye aberration by adaptive optics technology, and realize the confocal scanning imaging function in a large field of view and the adaptive optics high-resolution imaging function in a small field of view simultaneously by the common beam synchronous scanning configuration combined with the two relay optical path structures for both the small field of view and the large field of view. The system can not only observe disease lesions in a wide range on the retina by the large field-of-view imaging, but also observe fine structures of the lesions by the small field-of-view high-resolution imaging. A variety of imaging images are acquired by common path optical beam scanning to meet the needs of different application scenes, which greatly expands the application range of the existing confocal imaging equipment.

In high-resolution scanning microscopy, a sample is excited by illumination radiation to emit fluorescence radiation in such a way that the illumination radiation is focused at a point in or on the sample to form a diffraction-limited illumination spot. The point is imaged in a diffraction-limited manner into a diffraction image on a spatially resolving surface detector, wherein the surface detector has a spatial resolution that resolves a structure of the diffraction image. The sample is scanned by means of different scanning positions with an increment of less than half the diameter of the illumination spot. An image of the sample is generated from the data of the surface detector and from the scanning positions assigned to said data, said image having a resolution that is increased beyond a resolution limit for imaging. For the purposes of distinguishing between at least two predetermined wavelength regions in the fluorescence radiation from the sample, a corresponding number of diffraction structures are generated on the surface detector for the at least two predetermined wavelength ranges, said diffraction structures differing but having a common center of symmetry. The diffraction structures are evaluated when generating the image of the sample.

An optical device may include an optical fiber having a fixed end and a free end a first actuator positioned at a actuator position between the fixed end and the free end and configured to apply a first force on the actuator position of the optical fiber such that a movement of the free end of the optical fiber in a first direction is caused, wherein the first direction is orthogonal to a longitudinal axis of the optical fiber; and a deformable rod disposed adjacent to the optical fiber, and having a first end and a second end, wherein the first end is connected to a first rod position of the optical fiber and the second end is connected to a second rod position of the optical fiber.

Disclosed herein are light sheet imaging systems for imaging fluorescent samples. Also disclosed herein are sample holder systems for high throughput light sheet imaging of multiple three-dimensional samples without user intervention. Further disclosed herein are automated image processing methods to identify and quantify fluorescent particles within three-dimensional image sets without user intervention or user bias.

A computing device, method, system, and instructions in a non-transitory computer-readable medium for performing image analysis on 3D microscopy images to predict localization and/or labeling of various structures or objects of interest, by predicting the location in such images at which a dye or other marker associated with such structures would appear. The computing device, method, and system receives sets of 3D images that include unlabeled images, such as transmitted light images or electron microscope images, and labeled images, such as images captured with fluorescence tagging. The computing device trains a statistical model to associate structures in the labeled images with the same structures in the unlabeled light images. The processor further applies the statistical model to a new unlabeled image to generate a predictive labeled image that predicts the location of a structure of interest in the new image.

The disclosure relates to a method for scanning microscopy wherein a specimen is scanned simultaneously with a plurality of illumination spots of an excitation light. The light emitted by one specimen location irradiated with one illumination spot is detected independently of the light emitted by another specimen location illuminated with another illumination spot. A microscopic image of the specimen can be compiled from the emitted light detected for the different specimen locations. The method provides that the intensities of the different illumination spots are set independently of one another, and in that the illumination spots are guided over the specimen one after another in a scan line. The disclosure additionally relates to a scanning microscope.