Abstract: An image acquire device comprising: an irradiator configured to irradiate an undyed tissue with excitation light; an image sensor configured to acquire a third harmonic image of the undyed tissue based on light generated in third harmonic generation caused by interaction between the undyed tissue and the excitation light.

Abstract: An image processor includes an image generator configured to generate corresponding image data corresponding to first microscopic image data obtained under a first observation condition, based on second microscopic image data and third microscopic image data obtained under a second observation condition, and an image output unit configured to output the corresponding image data. The corresponding image data may be image data corresponding to a first focal plane from which the first microscopic image data are obtained, and wherein the second microscopic image data and the third microscopic image data may be image data on a second focal plane and a third focal plane, respectively, which are different from the first focal plane.

Abstract: An image processor includes an image generator configured to generate corresponding image data corresponding to first microscopic image data obtained under a first observation condition, based on second microscopic image data and third microscopic image data obtained under a second observation condition, and an image output unit configured to output the corresponding image data. The corresponding image data may be image data corresponding to a first focal plane from which the first microscopic image data are obtained, and wherein the second microscopic image data and the third microscopic image data may be image data on a second focal plane and a third focal plane, respectively, which are different from the first focal plane.

Abstract: An image processor includes an image generator configured to generate corresponding image data corresponding to first microscopic image data obtained under a first observation condition, based on second microscopic image data and third microscopic image data obtained under a second observation condition, and an image output unit configured to output the corresponding image data. The corresponding image data may be image data corresponding to a first focal plane from which the first microscopic image data are obtained, and wherein the second microscopic image data and the third microscopic image data may be image data on a second focal plane and a third focal plane, respectively, which are different from the first focal plane.

Abstract: An image analysis device includes a first calculating part that calculates a magnitude of motion of an image element from time-series images of pulsating myocardial cells, a second calculating part that calculates a feature quantity on the basis of the magnitude of the motion of the image element calculated by the first calculating part, and an identifying part that identifies whether the image element is a predetermined image element on the basis of the feature quantity calculated by the second calculating part.

Abstract: An image analysis device includes a first calculating part that calculates a magnitude of motion of an image element from time-series images of pulsating myocardial cells, a second calculating part that calculates a feature quantity on the basis of the magnitude of the motion of the image element calculated by the first calculating part, and an identifying part that identifies whether the image element is a predetermined image element on the basis of the feature quantity calculated by the second calculating part.

Abstract: An image-processing program for cell observation comprises obtaining a first image showing a plurality of cells in an observation region, the first image being captured by an imaging device, and a second image showing the observation region, the second image being captured by the imaging device a predetermined time before the first image is captured; selecting one cell as a cell of interest from the plurality of cells included in the first image; specifying cells on the periphery of the cell of interest as peripheral cells; calculating movement statistics of the peripheral cells with respect to the cell of interest on the basis of the amount of relative movement of the cell of interest and the peripheral cells in the first image and the second image; and outputting the calculated movement statistics of the peripheral cells.

Abstract: An image processing device determines the degree of activity of a cell during cell viewing. An imaging device captures first and second images of a cell under observation. After aligning the rotational angle orientations on the image plane of the cell under observation that is included in the images, a correlation value or difference of intracellular texture feature values in the first image and second image, is sequentially computed. A time series variation of the computed correlation value or difference is then derived, and the degree of activity of the cell under observation is detected based on the state of variation.

Abstract: An image processing program (GP) attains (S10) time lapse images, extracts (S20) a cell aggregation from each of the obtained images, and calculates (S50), for the entire region of the cell aggregation, the spatial distribution in pixel values and temporal change in pixel values of a small region in the extracted cell aggregation. The program determines (S70) the state of change of the cell aggregation toward becoming multi-layered, on the basis of the calculated spatial distribution and time lapse change of pixel values, and outputs (S80) the results of the determination. The image processing program (GP) is configured so as to determine and output, from time lapse images, the state of change of the cell aggregation toward becoming multi-layered.

Abstract: An image-processing method for processing a time lapse image includes acquiring a first image obtained by capturing an image of an object located within a field of view using an imaging device and a second image obtained by capturing an image of the object located within the field of view using the imaging device after a predetermined time period has elapsed, calculating a positional correction value for a positional shift between the first image and the second image, by using a correlation function weighted according to an image feature of each of the objects included in the first image and the second image, and performing, based on the calculated positional correction value, a positional correction between the first image and the second image. The time lapse image is generated using the first image and the second image on which the positional correction has been performed.

Abstract: An image processing program for cell observation in which living cells can be distinguished from foreign matter other than living cells during cell observation under wide observation conditions. The image processing program includes a step for capturing first and second images of an object positioned in the observation field of view at a predetermined time interval, a step for extracting a representation of the object shown in the obtained images, steps for aligning the rotational angular orientation of the object in the image plane and computing a correlation value, a step for determining whether the object is a living cell on the basis of the computed correlation value, and steps for outputting the result of the decision made with regard to the object.

Abstract: An image processing program (GP) attains (S10) time lapse images, extracts (S20) a cell aggregation from each of the obtained images, and calculates (S50), for the entire region of the cell aggregation, the spatial distribution in pixel values and temporal change in pixel values of a small region in the extracted cell aggregation. The program determines (S70) the state of change of the cell aggregation toward becoming multi-layered, on the basis of the calculated spatial distribution and time lapse change of pixel values, and outputs (S80) the results of the determination. The image processing program (GP) is configured so as to determine and output, from time lapse images, the state of change of the cell aggregation toward becoming multi-layered.

Abstract: An image processing program AP comprises: a step (S1) of reading time-lapse images; a step (S2) of extracting cells in a viewing image from each time point and performing labeling and cell association; and a step (S3) of determining the maturity of a cell included in the viewing image from a designated time point tc. In step (S4), an ID is assigned for a cell determined to be mature, and in step (S5), ID inheritance is performed by cell tracking of the time-lapse images in the backward or forward direction of time along the time axis. In step (S6), the number of unifications of cells is computed, and cells are classified on the basis of the inherited ID information, and the results of analysis are outputted in step (S7).

Abstract: An image processing program (GP) is configured to comprise a step (A10) for obtaining time lapse images in which a cell aggregation is imaged over a predetermined time interval by an imaging device, a step (A20) for sequentially calculating a feature value relating to multi-layering of the cell aggregation from the obtained time lapse images, a step (A30) for deriving time lapse changes in the calculated feature value relating to the multi-layering, and a step (A40) for outputting the derived time lapse changes in the multi-layering feature values.

Abstract: An image processing program obtains a first image and a second image taken by an imaging device at a predetermined time interval; performs block matching, using the luminance distribution of a local region of the first image as a standard, in a vicinity including the corresponding position of the second image, taking the degree of approximation of the region with the highest degree of matching as a representative degree of approximation, sequentially moving the local region, and calculating the representative degree of approximation for individual parts of the cell aggregation; and outputting multi-layering information corresponding to the calculated representative degree of approximation. The image processing program outputs multi-layering information by which the state of change of the cell aggregation toward becoming multi-layered can be decided from the first and second images.

Abstract: A spectral image processing method is capable of reducing noise while maintaining necessary information. The spectral image processing method performs processing on a spectral image of a specimen, including a step of normalizing spectra (=spectral brightness curves) of respective pixels constituting the spectral image such that their brightness levels become equal, a step of smoothing the normalized spectra in spatial directions of the respective pixels, and a step of denormalization of multiplying spectra of the respective pixels obtained by the smoothing by either one of brightness levels of the pixels corresponding the spectra and values corresponding to the brightness levels. Consequently, the noise can be reduced while information on brightness distribution on the image is maintained.

Abstract: A spectral image processing system and method of performing robust unmixing on measurement noise. Based on an observed spectral image acquired from a specimen and emission spectral data of each of plural materials contained in the specimen, a contribution of each of the plural materials to the observed spectral image is unmixed by a process, including an evaluating step of evaluating reliability of each component of the observed spectral image based on a predicted spectral image of the observed spectral image, and a reflecting step of reflecting a result of the evaluation in a content of the unmixing.

Abstract: Provided is a means whereby the degree of activity of a cell can be determined during cell viewing. By an imaging device, first and second images in which a cell under observation is captured are sequentially obtained at a predetermined time interval, and after aligning the rotational angle orientations on the image plane of the cell under observation that is included in the images, a correlation value or difference of intracellular texture feature values in the first image and second image is sequentially computed. A time series variation of the computed correlation value or difference is then derived, and the degree of activity of the cell under observation is detected based on the state of variation.

Abstract: The contour of a cell being observed is extracted from a cell observation image obtained by an imaging device, and a cell model made by modeling the outer shape of the cell is adapted. The direction in which the cell being observed is predicted to move is derived using the adapted cell model.

Abstract: An image-processing program for cell observation comprises obtaining a first image showing a plurality of cells in an observation region, the first image being captured by an imaging device, and a second image showing the observation region, the second image being captured by the imaging device a predetermined time before the first image is captured; selecting one cell as a cell of interest from the plurality of cells included in the first image; specifying cells on the periphery of the cell of interest as peripheral cells; calculating movement statistics of the peripheral cells with respect to the cell of interest on the basis of the amount of relative movement of the cell of interest and the peripheral cells in the first image and the second image; and outputting the calculated movement statistics of the peripheral cells.