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 pharmaceutical filling system for a high volume pharmacy is described. The system can include a spill detection subsystem and method. The system can include a cameras to take images that a processed to determine presence of a spilled pharmaceutical. A mirror portion is provided so that the camera can take images of the entire field of the filling area. The mirror portion can be a concave mirror that increases the field of view of the camera. A light panel can illuminate the field of view to allow the camera to take high speed images. A controller can receive a series of at least two images captured by the camera and determine whether an object in the captured images is a spilled pharmaceutical.

A medical image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry acquires image data including image data of a blood vessel of a subject. The processing circuitry performs analysis related to the blood vessel by using the image data, and specifies a region of interest in the blood vessel based on a result of the analysis. The processing circuitry performs fluid analysis on a region other than the region of interest at a first accuracy, and performs fluid analysis on the region of interest at a second accuracy that is higher than the first accuracy.

A system and method for developing applications (Apps) for automated assessment and analysis of processed biological samples. Such samples are obtained, combined with nutrient media and incubated. The incubated samples are imaged and the image information is classified according to predetermined criteria. The classified image information is then evaluated according to Apps derived from classified historical image information in a data base. The classified historical image information is compared with the classified image information to provide guidance on further processing of the biological sample through Apps tailored to process provide sample process guidance tailored to the classifications assigned to the image information.

A method and system for image processing are provided. An MR image including a plurality of slice images may be obtained. The plurality of slice images including a myocardium of a left ventricle. A reference image for each slice image of the plurality of slice images may be determined. An endocardial boundary of the myocardium for the each slice image of the plurality of slice images may be determined. The each slice image of the plurality of slice images may be registered according to a corresponding reference image. An epicardial boundary of the myocardium in the each slice image of the plurality of slice images may be determined according to the endocardial boundary of the myocardium in the registered each slice image of the plurality of slice images.

According to some aspects, an image processing apparatus is provided. The image processing apparatus includes circuitry configured to receive at least two images of at least one cell. The at least two images are captured at different times. The circuitry is further configured to determine a motion amount of at least one intracellular structure identified within the at least one cell by comparing the at least two images and generate an indication of cell metabolism information associated with the at least one cell by relating at least one parameter of the motion amount to a degree of cell metabolism for the at least one cell based on reference information.

A system for registering and segmenting images includes an image scanner configured to acquire an image pair including a first image at a first time and a second image at a second time that is after the first time. A joint registration and segmentation server receives the image pair from the image scanner and simultaneously performs joint registration and segmentation on the image pair using a single deep learning framework. A computer vision processor receives an output of the joint registration and segmentation server and characterizes how a condition has progressed from the first time to the second time therefrom. A user terminal presents the characterization to a user.

Medical imaging device- and display-invariant segmentation and measurement is provided. In various embodiments, a plurality of medical images is read from a data store. Metadata of each of the plurality of medical images is read. The metadata identifies an image acquisition device associated with each of the plurality of medical images. Based on the plurality of medical images and the metadata of each of the plurality of images, a learning system is trained to determine one or more image correction parameters. The one or more image correction parameters optimize segmentation of the plurality of medical images.

A heart rate detection method includes a facial image data acquiring step, a feature points recognizing step, an effective displacement signal generating step and a heart rate determining step. The feature points recognizing step is for recognizing a plurality of feature points, wherein a number range of the feature points is from three to twenty, and the feature points include a center point between two medial canthi, a point of a pronasale and a point of a subnasale of the face. The effective displacement signal generating step is for calculating an original displacement signal, wherein the original displacement signal is converted to an effective displacement signal. The heart rate determining step is for transforming the effective displacement signals of each of the feature points to an effective spectrum, wherein a heart rate is determined from one of the effective spectrums corresponding to the feature points, respectively.

A culture information processing device includes: a feature value computing unit that computes growth feature values indicating features of growth characteristics of cells from data acquired in a particular first subculturing process selected from among a plurality of subculturing processes included in a culture period of the cells; a condition setting unit that sets culturing conditions of a second subculturing process one process after the first subculturing process; and an information computing unit that computes, on the basis of the growth feature values computed by the feature value computing unit and the culturing conditions set by the condition setting unit, characteristics-related information related to growth characteristics in the second subculturing process.