A non-invasive method of evaluating blood cell measurement and a non-invasive blood cell measurement evaluating system are provided. The non-invasive method of evaluating blood cell measurement includes providing of a dialysis tubing image datum of a subject, performing an image preprocessing step, performing a model predicting step and performing a determining and classifying step. The non-invasive blood cell measurement evaluating system includes an image capturing device and a processor electrically connected to the image capture device.

The present disclosure generally relates to the field of deep learning technologies. An apparatus for generating a plurality of correlation images may include a feature extracting unit configured to receive a training image and extracting at least one or more of feature from the training image to generate a first feature image based on the training image; a normalizer configured to normalize the first feature image and generate a second feature image; and a shift correlating unit configured to perform a plurality of translational shifts on the second feature image to generate a plurality of shifted images, correlate each of the plurality of shifted images with the second feature image to generate the plurality of correlation images.

In one embodiment, an X-ray inspection system may access a first set of X-ray images of one or more first samples that are labeled as being non-conforming. The system may adjust a classification algorithm based on the first set of X-ray images. The classification algorithm may classify samples into conforming or non-conforming categories based on an analysis of corresponding X-ray images. The system may analyze a second set of X-ray images of a number of second samples using the adjusted classification algorithm. The second samples may be previously inspected samples that have been classified as conforming by the classification algorithm during a previous analysis before the classification algorithm is adjusted. The system may identify one or more of the second samples from the second set of X-ray images. Each identified second sample may be classified as non-conforming by the adjusted classification algorithm.

A fluorescence imaging system is configured to generate a video image onto a display. The system includes a light source for emitting infrared light and white light, an infrared image sensor for capturing infrared image data, and a white light image sensor for capturing white light image data. Data processing hardware performs operations that include filtering the infrared image data with a first digital finite impulse response (FIR) filter configured to produce a magnitude response of zero at a horizontal Nyquist frequency and a vertical Nyquist frequency. The operations also include filtering the infrared image data with a second digital FIR filter configured with a phase response to spatially align the white light image data with the infrared image data. The operations also include combining the white light image data and the infrared image data into combined image data and transmitting the combined image data to the display.

The disclosure provides a method, device, and readable storage medium for adjusting image quality. The display device system selects a focus area of a target image, and outputs a mapping relationship curve of an input luminance value and an output luminance value of the target image. Then, an input luminance value range of pixels in the focus area of the target image is calculated, and upper and lower edge coefficients of the input luminance value range are proportionally adjusted to obtain new upper and lower edge coefficients. The mapping relationship curve is adjusted according to the new upper and lower edge coefficients, thereby adjusting the focus area of the target image.

A smart camera for an electronic monitoring system is provided. The smart camera includes an imaging device having a field of view and being configured to capture an image. The imaging device has a variable exposure. A detector is operatively connected to the imaging device and configured to generate a trigger signal in response to activity within the field of view. A first processor is operatively connected to the detector and the imaging device, and a second processor is operatively connected to the detector and the imaging device. A computer-readable memory is operatively connected to the first processor and the secondary processor. The computer-readable memory is configured to store a map of ambient light levels in the field of view at selected times of day. The second processor varies the exposure of the imaging device in response to the trigger signal.

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to obtain contrast-enhanced images related to an examined subject and corresponding to a plurality of temporal phases. On the basis of data values of pixels in the contrast-enhanced images corresponding to the plurality of temporal phases, the processing circuitry is configured to determine which one of contrast enhancement dominance and fluid accumulation dominance corresponds to the pixels or a region including the pixels. The processing circuitry is configured to generate a display mode based on the determination.

An image capturing device with a sensor, a memory, and a processor is provided. The sensor captures an image of at least one target. The memory stores a plurality of instructions. The processor obtains the plurality of instructions to perform the following steps: controlling the sensor to capture a reference image and a processed image; capturing a first bright region and a dark region from the reference image, and capturing a second bright region from the processed image; performing calculations on a first brightness value of the first bright region and a second brightness value of the second bright region respectively with at least two first brightness thresholds, to obtain a first low exposure compensation value and a second low exposure compensation value; and obtaining a high exposure compensation value according to comparisons between a third brightness value of the dark region and at least two second brightness thresholds.

A method for processing an image includes: creating M first image sets based on M image frames to be processed; determining a fusion weight for each sub-image located in each layer in each first image set based on brightness information of each image frame; fusing sub-images located in each same layer in the M first image sets based on the fusion weight, to obtain N fused sub-images arranged in layers based on the preset order; adjusting a brightness of at least one fused sub-image of the N fused sub-images based on a preset brightness adjustment parameter; and obtaining a target image based on the fused sub-image after adjustment.

A system including image sensor(s) including a plurality of pixels arranged on a photo-sensitive surface thereof; and image signal processor(s) configured to: receive, from image sensor(s), a plurality of image signals captured by corresponding pixels of image sensor(s); and process the plurality of image signals to generate at least one image, wherein, when processing, image signal processor(s) is configured to: determine, for a given image signal to be processed, a position of a given pixel on the photo-sensitive surface that is employed to capture the given image signal; and selectively perform a sequence of image signal processes on the given image signal and control a plurality of parameters employed for performing the sequence of image signal processes, based on the position of the given pixel.