Lighting systems and associated controls that can provide active control of lighting device settings, such as on/off, color, intensity, focal length, beam location, beam size and beam shape. In some examples, lighting systems may include eye tracking technology and sensor feedback for one or more lighting device settings and may be configured with depth perception and cavity or incision recognition capability through image or video processing.

An imaging system includes an image sensing unit and a processing unit. The image sensing unit captures a plurality of images of an object, wherein each of the images includes a plurality of pixels. The processing unit obtains a plurality of sets of image data according to the images, wherein each set of image data includes a plurality of characteristic values. The processing unit calculates a plurality of difference parameters of the characteristic values of every two sets of image data. The processing unit accumulates the difference parameters within a predetermined time period to obtain a plurality of accumulated difference parameters corresponding to the pixels. The processing unit determines a plurality of weighting values corresponding to the pixels according to the accumulated difference parameters. The processing unit performs an image processing process according to the sets of image data and the weighting values.

A brain tumor image segmentation method and device are disclosed. The disclosed method includes acquiring a basic white matter template generated based on brain magnetic resonance images of a plurality of healthy samples, collecting corresponding low, mid and high b-value diffusion weighted images of the brain of a patient, segmenting out a tumor region including the tumor body and the edema on each image based on the signal distribution of each image in a first set image group of the patient, removing the normal white matter region from the tumor region according to the basic white matter template and the high b-value diffusion weighted image, and classifying the value of the voxel in each image in a second set image group and a second apparent diffusion coefficient image obtained through calculations to obtain a tumor body region and an edema region.

A difference image generation unit generates a difference image between first and second three-dimensional images. A combining unit generates a composite image in which the difference image is superimposed on at least one of the first three-dimensional image or the second three-dimensional image. A range specifying unit specifies a generation range of the difference image in a direction, in which the tomographic images are arranged, in at least one of the first three-dimensional image or the second three-dimensional image. A display controller displays the composite image on a display unit. In this case, first information indicating a generation range of each of the tomographic images and second information indicating the generation range of the difference image are displayed.

Method of defining at least one treatment area including receiving a first set of data from a digital geometric representation of a target area; receiving a second set of data representing at least a portion of an applicator designed to contact the target area; digitally overlying the second set of data over the first set of data to generate a first digital overlay; digitally defining a treatment area on the first digital overlay surrounding the condition; generating a third set of data representing a portion of the applicator and the treatment area; digitally overlying the third set of data over the first set of data to generate a second digital overlay representing coverage of a condition by the treatment area; and generating a first electronic image that includes a visual depiction of the second digital overlay.

The present disclosure relates to a data processing apparatus and a data processing method capable of generating evaluation index data for performing accurate and detailed evaluation of cultured cardiomyocytes. A motion detecting unit divides frame image data obtained by photographing the cultured cardiomyocytes for a predetermined time into blocks and obtains motion detection data in units of blocks per each frame period. A feature amount calculating unit calculates a feature amount for each block at the same position in a frame image using the motion detection data. A classification processing unit classifies each of the blocks into any one of a plurality of classification categories using the calculated feature amount. On the basis of the classification result, evaluation index data made of individual classification result data that represent correspondences between the blocks and the classification categories is generated.

An imaging system and method for microbial growth detection, counting or identification. One colony may be contrasted in an image that is not optimal for another type of colony. The system and method provides contrast from all available material through space (spatial differences), time (differences appearing over time for a given capture condition) and color space transformation using image input information over time to assess whether microbial growth has occurred for a given sample.

An image processing apparatus includes: an obtaining unit configured to obtain a first image of an object and a second image of the object; a difference unit configured to obtain a difference image after the first image and the second image are registered; and a change unit configured to perform processing of changing a pixel value in the difference image based on a likelihood calculated using a pixel value in the first image and a pixel value in the second image.

Methods and apparatus are disclosed that assist a user in tracking changes that occur in an anatomical region of one or more subjects based on three-dimensional images of the region captured at different times, such as before and after treatment. In exemplary implementations, a three-dimensional anatomical reference model derived from a population of relevance to the subjects is deformed to fit at least a baseline image of each of the subjects. The deformed model of each subject's baseline image is further deformed to fit a follow-up image of the subject's anatomical region. The deformed models thus generated are used to establish sparse correspondences between the images from which surrounding, denser correspondences between the images are additionally found.

A framework for quantitative evaluation of time-varying data. In accordance with one aspect, the framework delineates a volume of interest in a four-dimensional (4D) Digital Subtraction Angiography (DSA) dataset (204). The framework then extracts a centerline of the volume of interest (206). In response to receiving one or more user-selected points along the centerline (208), the framework determines at least one blood dynamics measure associated with the one or more user-selected points (210), and generates a visualization based on the blood dynamics measure (212).