WO2015182382A1 - 細胞評価装置および方法並びにプログラム - Google Patents
細胞評価装置および方法並びにプログラム Download PDFInfo
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Definitions
- the present invention relates to a cell evaluation apparatus, method, and program for evaluating individual cells in a cell image obtained by imaging a cell group.
- pluripotent stem cells such as ES cells and iPS cells and differentiation-induced cells are cultured, imaged with a microscope, and the state of the cells is evaluated by capturing the characteristics of the images.
- the cultured cells reach colony as the culture progresses and proliferate over a large area.
- Cell sizes are on the order of micrometers, and colony sizes range from a few millimeters to a few centimeters.
- individual cells are nucleated red blood cells (NRBCs) based on feature amounts calculated from images of individual cells and learning parameters learned in advance. A method of identifying whether or not is is proposed.
- NRBCs nucleated red blood cells
- FIGS. 13A and 13B are enlarged views of part of the cell image of the colonized cell group.
- a range surrounded by a solid line in FIG. 13A and a range surrounded by a broken line in FIG. 13B are individual cells.
- FIGS. 13A and 13B cells having similar shapes tend to gather around.
- Patent Document 2 when evaluating the degree of differentiation of a cell colony, it has been proposed to use the morphological feature amount of a feeder cell existing around the cell colony. None has been proposed about how to evaluate.
- an object of the present invention is to provide a cell evaluation apparatus, method, and program capable of highly accurately evaluating individual cells in a cell image obtained by imaging a cell group.
- the cell evaluation apparatus includes an image acquisition unit that acquires a cell image obtained by imaging a cell group, an individual cell in the cell group, a cell to be evaluated among the recognized individual cells, and an evaluation target thereof And a cell evaluation unit that determines the evaluation of the evaluation target cell based on the evaluation result of the surrounding cell and the evaluation result of the evaluation target cell. To do.
- the cell evaluation unit may determine the evaluation of the evaluation target cell based only on the evaluation result of the cells that can be evaluated among the evaluation results of the surrounding cells. Good.
- the cell evaluation unit is based on at least one of the size or shape of the cell nucleus of the cell to be evaluated, the size or shape of the cytoplasm, the size or shape of the nucleolus, the cell growth rate and the migration rate, A region for specifying surrounding cells may be determined, and cells including all or part of the region may be specified as surrounding cells.
- the cell evaluation unit may expand the area until the number of cells existing in the area for specifying surrounding cells reaches a preset number.
- the cell evaluation unit may expand the region in the vertical direction and the horizontal direction of the cell image.
- the cell evaluation unit may determine the aspect ratio of the region in the vertical direction and the horizontal direction.
- the cell evaluation unit may determine the number of cells searched in the vertical direction and the number of cells searched in the horizontal direction when expanding the region.
- the cell evaluation unit may set weighting for the evaluation result of the surrounding cells based on the distance between the evaluation target cell and the surrounding cells.
- the cell evaluation unit may evaluate the undifferentiated state or the differentiated state of the cell to be evaluated.
- the cell evaluation unit may evaluate the degree of differentiation of the cell to be evaluated.
- a boundary setting unit that sets a boundary in the cell image based on the state of the cell group is provided, and the cell evaluation unit, when specifying the surrounding cells, of the plurality of divided regions divided by the boundary Only cells present in the divided region where the cells exist may be specified as surrounding cells.
- the cell evaluation method of the present invention acquires a cell image obtained by imaging a cell group, recognizes individual cells in the cell group, and the evaluation target cells of the recognized individual cells and surroundings of the evaluation target cells And evaluating the evaluation target cell based on the evaluation result of the surrounding cell and the evaluation result of the evaluation target cell.
- the cell evaluation program includes a computer, an image acquisition unit that acquires a cell image obtained by imaging a cell group, an individual cell in the cell group, and an evaluation target cell among the recognized individual cells. Identify the cells surrounding the cell to be evaluated, and function as a cell evaluation unit that determines the evaluation of the cell to be evaluated based on the evaluation result of the surrounding cell and the evaluation result of the cell to be evaluated It is characterized by.
- a cell image obtained by imaging a cell group is acquired, an individual cell in the cell group is recognized, and a cell to be evaluated among the recognized individual cells Since the cells surrounding the cells to be evaluated are identified and the cells to be evaluated are evaluated based on the evaluation results of the surrounding cells, the evaluation results of the surrounding cells having similar characteristics are evaluated. This can be reflected in the evaluation result of the target cell, and thus the evaluation target cell can be evaluated with higher accuracy.
- the block diagram which shows schematic structure of the cell culture observation system using 1st Embodiment of the cell evaluation apparatus of this invention.
- Diagram showing schematic configuration of phase contrast microscope The figure which shows an example of the cell image of the cell group containing an undifferentiated stem cell and a differentiated stem cell The figure which shows an example of the boundary set in the cell image shown in FIG.
- Diagram for explaining how to identify surrounding cells Diagram for explaining how to identify surrounding cells
- Diagram for explaining how to identify surrounding cells Diagram for explaining how to identify surrounding cells
- the figure for explaining the other setting method of the peripheral region of the evaluation object cell The flowchart for demonstrating the effect
- the block diagram which shows schematic structure of the cell culture observation system using 2nd Embodiment of the cell evaluation apparatus of this invention.
- FIG. 1 is a block diagram showing a schematic configuration of a cell culture observation system.
- the cell culture observation system of the present embodiment includes a cell culture device 1, an imaging device 2, a cell evaluation device 3, a display 4, and an input device 5, as shown in FIG.
- the cell culture device 1 is a device for culturing cells.
- Examples of cells to be cultured include pluripotent stem cells such as iPS cells and ES cells, cells such as nerves, skin, myocardium, and liver induced by differentiation from stem cells, and cancer cells.
- pluripotent stem cells such as iPS cells and ES cells
- cells such as nerves, skin, myocardium, and liver induced by differentiation from stem cells, and cancer cells.
- a plurality of culture containers in which cells to be cultured are seeded in a medium are accommodated.
- the cell culture device 1 includes a stage 10, a transport unit 11, and a control unit 12.
- Stage 10 is where a culture vessel to be imaged by the imaging device 2 is installed.
- the transport unit 11 selects a culture container to be imaged from among a plurality of culture containers accommodated at a predetermined position in the cell culture apparatus 1, and transports the selected culture container to the stage 10.
- the control unit 12 controls the entire cell culture device 1.
- the controller 12 moves the stage 10 in the XY directions perpendicular to each other on the installation surface of the culture vessel, and the imaging region of the phase contrast microscope 20 described later is changed by this movement.
- the control unit 12 in addition to the operation of the stage 10 and the conveying unit 11 described above, is to control the temperature in the cell culture apparatus 1, the environmental conditions such as humidity and CO 2 concentration.
- the temperature, the configuration for adjusting the humidity and CO 2 concentration can be a known configuration.
- the imaging device 2 captures an image of a cell group in a culture vessel installed on the stage 10.
- the imaging device 2 includes a phase contrast microscope 20 that captures a cell group and outputs a cell image, and a control unit 29 that controls the phase contrast microscope 20.
- the phase contrast microscope 20 captures a phase image of the cells in the culture vessel installed on the stage 10.
- FIG. 2 is a diagram showing a schematic configuration of the phase-contrast microscope 20.
- the phase-contrast microscope 20 has an illumination light source 21 that emits illumination light and a ring-shaped slit, and the illumination light emitted from the illumination light source 21 is incident to emit ring-shaped illumination light.
- an objective lens that irradiates the cells in the culture vessel 15 installed on the stage 10 with the ring-shaped illumination light emitted from the slit plate 22. 23.
- a phase difference lens 24, an imaging lens 27, and an image sensor 28 are provided on the opposite side of the stage 10 from the illumination light source 21.
- the phase difference lens 24 includes an objective lens 25 and a phase plate 26.
- the phase plate 26 is obtained by forming a phase ring on a transparent plate that is transparent to the wavelength of the ring-shaped illumination light.
- the slit size of the slit plate 22 described above is in a conjugate relationship with this phase ring.
- the phase ring is a ring in which a phase film that shifts the phase of incident light by a quarter wavelength and a neutral density filter that attenuates incident light are formed.
- the direct light incident on the phase difference lens 24 is collected by the objective lens 25 and passes through the phase ring so that the phase is shifted by a quarter wavelength and the brightness is weakened.
- most of the diffracted light diffracted by the cells in the culture vessel 15 passes through the transparent plate of the phase plate, and its phase and brightness do not change.
- the phase difference lens 24 is moved in the direction of arrow A shown in FIG. 2 by a driving mechanism (not shown). As the phase difference lens 24 moves in this way, the focus position is changed and focus control is performed.
- the drive mechanism moves the phase difference lens 24 based on the focus control signal output from the control unit 29.
- phase contrast microscope 20 of the present embodiment is configured such that a plurality of phase difference lenses 24 having different optical magnifications can be exchanged.
- the phase difference lens 24 may be replaced automatically according to an instruction input from the user, or may be replaced manually by the user.
- the imaging lens 27 receives direct light and diffracted light that have passed through the phase difference lens 24 and forms an image of these lights on the image sensor 28.
- the imaging element 28 captures a phase image of the cell by photoelectrically converting the image formed by the imaging lens 27.
- a charge-coupled device (CCD) image sensor, a complementary metal-oxide semiconductor (CMOS) image sensor, or the like is used as the image sensor 28 .
- the phase contrast microscope is used.
- the present invention is not limited to this.
- a bright field microscope or a differential interference microscope may be used.
- the control unit 29 controls the entire imaging apparatus 2. Specifically, the control unit 29 controls the optical magnification of the phase contrast microscope 20, the exposure time of the image sensor 28, the illumination light wavelength of the illumination light source, the observation light wavelength, and the like.
- the illumination light wavelength of the illumination light source for example, when the illumination light source is composed of LED (Light Emitting Diode) or LD (Laser Diode), the illumination light wavelength is changed by changing the drive current. Also good. Further, a plurality of illumination light sources having different illumination light wavelengths may be provided, and the illumination light wavelength may be changed by switching these light sources. Further, the observation light wavelength may be changed using a filter, a spectroscope, or the like not shown.
- the cell evaluation apparatus 3 is one in which an embodiment of the cell evaluation program of the present invention is installed in a computer.
- the cell evaluation apparatus 3 includes a central processing unit, a semiconductor memory, a hard disk, and the like, and one embodiment of the cell evaluation program of the present invention is installed on the hard disk. Then, when this program is executed by the central processing unit, the image acquisition unit 30, the boundary setting unit 31, the cell evaluation unit 32, and the display control unit 33 as shown in FIG. 1 operate.
- the image acquisition unit 30 acquires and stores the cell image of the cell group imaged by the imaging device 2.
- a cell image obtained by imaging a cell group is acquired by setting the optical magnification of the phase-contrast microscope 20 to 4 to 20 times.
- the boundary setting unit 31 sets a boundary in the cell image based on the state of the cell group in the cell image.
- the boundary setting unit 31 of the present embodiment for example, in a cell group of stem cells, includes a region where a differentiated stem cell is distributed and a region where an undifferentiated stem cell is distributed. A differentiated area is determined, and a boundary between the differentiated area and the undifferentiated area is set.
- FIG. 3 is a diagram showing an example of a cell image of a cell group including undifferentiated stem cells and differentiated stem cells. As shown in FIG. 3, when an undifferentiated stem cell is compared with a differentiated stem cell, the undifferentiated stem cell has a higher circularity than the differentiated stem cell, and the differentiated stem cell is undifferentiated. It is longer and larger than the stem cells in the state.
- the boundary setting unit 31 calculates the spatial frequency of the cell image and undifferentiates an area where the spatial frequency is equal to or greater than a predetermined threshold. An area is determined, and an area having a spatial frequency less than the threshold is determined as a differentiated area.
- the differentiated region and the undifferentiated region may be determined using a luminance change or a color change. For example, as shown in FIG. 3, in the region where stem cells in an undifferentiated state are distributed, stem cells are dense, and halo is generated at the boundary between the stem cells, resulting in high brightness. Halo is a high-luminance artifact that occurs when illumination light passes between cells.
- the boundary setting unit 31 calculates the luminance change of the cell image, determines an area where the luminance change is equal to or greater than a predetermined threshold as an undifferentiated area, and determines an area where the luminance change is less than the threshold as a differentiated area. Also good. In addition, the boundary setting unit 31 calculates a color change of the cell image, determines an area where the color change is equal to or greater than a predetermined threshold as an undifferentiated area, and the color change is less than the threshold. The region may be determined as a differentiated region.
- the boundary setting unit 31 may calculate the luminance of the cell image, determine an area where the luminance is equal to or higher than a predetermined threshold as an undifferentiated area, and determine an area where the luminance is lower than the threshold as a differentiated area.
- the differentiated region and the undifferentiated region may be determined by combining at least two features of spatial frequency, luminance, and color.
- one evaluation value is calculated by weighting and adding each of a plurality of features, and a differentiated region and an undifferentiated region are determined based on whether the evaluation value is greater than or less than a threshold value. You may do it.
- the boundary setting unit 31 calculates a feature amount over the entire cell image such as a spatial frequency, a luminance change, and a color change, and roughly divides the cell group based on the feature amount. Set.
- the boundary set in the present embodiment is not a strict boundary but may be a boundary that roughly divides a cell group, and is preferably more linear.
- an upper limit such as the number of inflection points or curvature of the boundary may be set, and a line segment having a smaller number of inflection points or a smaller curvature than the upper limit may be set as the boundary.
- a plurality of boundary candidate line segments may be extracted, and the boundary candidates that do not exceed the above-described upper limit may be set as the final boundary.
- FIG. 4 is a diagram showing an example of a boundary set in the cell image shown in FIG.
- a line segment indicated by an alternate long and short dash line is a boundary set by the boundary setting unit 31.
- the boundary setting unit 31 sets the boundary between the undifferentiated region and the differentiated region.
- the boundary set by the boundary setting unit 31 is limited to the boundary between the undifferentiated region and the differentiated region. I can't.
- the boundary may be set according to the degree of differentiation of the cell. For example, a boundary may be set between a region where the degree of differentiation is greater than or equal to a predetermined threshold and a region where the degree of differentiation is less than the threshold.
- a cell group is a cancer cell, you may make it set a boundary according to the malignancy of the cancer cell. For example, a boundary may be set between a region where the malignancy is greater than or equal to a predetermined threshold and a region where the malignancy is less than the threshold.
- the cell evaluation unit 32 specifies cells to be evaluated in the cell group in the cell image and cells around the cells to be evaluated, and uses the evaluation results of the specified surrounding cells, The cells to be evaluated are evaluated.
- the cell evaluation unit 32 when evaluating the state of individual cells based on the cell image, it may not be possible to properly evaluate the state by focusing on only the individual cell images. Therefore, when evaluating the evaluation target cell, the cell evaluation unit 32 also acquires the evaluation result of the surrounding cell, and uses the evaluation result of the surrounding cell and the evaluation result of the evaluation target cell to perform the evaluation. Perform an assessment of the cells in question and confirm the assessment.
- a method for evaluating individual cells will be specifically described.
- the cell evaluation unit 32 first identifies individual cells included in the cell image.
- an individual cell identification method for example, after converting a cell image into a binarized image, filtering process is performed to detect the edge of each cell, and pattern matching is performed on the edge. Should be specified. Moreover, it is desirable to perform pattern recognition using machine learning at the time of pattern matching. However, it is not limited to such a method, and various known methods can be used.
- the cell evaluation unit 32 evaluates each individual cell specified as described above as to whether it is in a differentiated state or an undifferentiated state.
- the final evaluation of the cell to be evaluated is determined using the result of the evaluation of the surrounding cells.
- a method for identifying cells around the cell to be evaluated will be described.
- a rectangular area that touches the outline of a predetermined evaluation target cell (indicated by a solid oval) is set, and the same size as the set rectangular area
- the rectangular area is set around the rectangular area of the cell to be evaluated, and the cells (indicated by dotted ellipses) that are all or part of the eight rectangular areas are specified as surrounding cells. That's fine.
- the evaluation target cell is an undifferentiated region. May exist in the vicinity of the boundary between the region and the differentiation region. In such a case, when a peripheral region is set across the boundary, both differentiated cells and undifferentiated cells are mixed as cells around the cell to be evaluated, and the cells to be evaluated An undifferentiated state or a differentiated state may not be properly evaluated.
- the cell evaluation unit 32 of the present embodiment acquires boundary information set by the boundary setting unit 31 and resets the peripheral region based on the boundary information.
- the peripheral region is selected so that only cells in the differentiated region are identified as surrounding cells. Reset it. Specifically, the above eight rectangular areas are reset so as to be arranged in the differentiated area.
- the method for resetting the peripheral area is not limited to the example shown in FIG. 7, and other methods may be adopted as long as all the peripheral areas are arranged in the differentiated area.
- the evaluation results of only the cells in the divided area where the cells to be evaluated exist can be used. Thereby, the undifferentiated state or differentiated state of the cell to be evaluated can be evaluated with higher accuracy.
- a rectangular area that is in contact with the outline of the cell to be evaluated is set, and a rectangular area having the same size as this rectangular area is set in the periphery. That is, the size of the cytoplasm of the cell to be evaluated is set.
- the size of the surrounding rectangular area is set based on the shape, the setting method of the surrounding area is not limited to this.
- the cell nucleus or nucleolus of the cell to be evaluated is detected, and the surrounding area is set according to the size or shape of the cell nucleus or nucleolus. You may make it identify as a cell.
- FIG. 8 is a diagram showing an example when the peripheral region is set wider as the cell nucleus is larger, for example.
- FIG. 9 is a diagram showing an example when the peripheral region is also changed in shape according to the shape of the cell nucleus. It is. The same applies when the peripheral region is set based on the size and shape of the nucleolus.
- the cells are extracted from the plurality of cell images. It is also possible to acquire information relating to the growth speed of the mouse, information relating to the migration speed, and the like, and to set the peripheral region based on these.
- cells with a fast growth rate are considered to have cells in a similar state distributed in a wider range. Therefore, a larger peripheral region may be set as the proliferation rate increases.
- the number of cells per unit area included in cell images taken at different times is counted, and the number of cells is increased and the imaging interval is used.
- the growth rate may be calculated.
- the unit area may be the entire cell image, or may be a partial region including cells to be evaluated.
- the area of each cell group included in the cell images taken at different times is calculated, and the area increase rate is used as information on the growth rate. You may make it acquire.
- the movement distance of the cell to be evaluated included in the cell images taken at different times is calculated, and the migration speed is calculated based on the movement distance and the imaging interval. What should I do?
- cells having similar cell shapes and existing in a preset range may be associated with each other. Further, other known methods may be used.
- the migration speed may be calculated based on the movement distance of all the cells included in the cell image. For example, a statistical value such as an average value, maximum value, or minimum value of the moving distance of each cell may be calculated, and the migration speed may be calculated based on the statistical value and the imaging interval.
- the above-described statistical value of the movement distance may be acquired as information on the migration speed.
- the peripheral region when setting a peripheral region for identifying surrounding cells, the peripheral region may be expanded until the number of surrounding cells included in the peripheral region reaches a preset number. .
- a desired number of surrounding cells can always be specified regardless of the density of the cells, so that the evaluation accuracy of the evaluation target cells can be stably improved. it can.
- the vertical and horizontal aspect ratios of the expansion width of the rectangular area may be the same or different.
- the aspect ratio may be the same. If the target cytoplasm, nucleus, or nucleolus has an elliptical shape that extends in the vertical or horizontal direction, the aspect ratio should be set so that the expansion width in the extending direction is relatively large. It may be.
- the aspect ratio may be set so that the expansion width in the direction in which the growth rate is fast becomes relatively large. Further, when the peripheral area of the rectangular area is set based on the traveling speed, the aspect ratio may be set so that the expansion width in the direction in which the traveling speed is fast becomes relatively large.
- the number of cells to be searched in the vertical direction and the cells to be searched in the horizontal direction may be the same or different.
- a search may be made by expanding the peripheral region in the radial direction with the cell to be evaluated as the center instead of the aspect ratio of the vertical and horizontal directions.
- the number of cells to be searched in the vertical direction and the horizontal direction may be the same. Good. If the cytoplasm, nucleus, or nucleolus of the evaluation target has an elliptical shape that extends in the vertical or horizontal direction, the number of cells to be searched in the extending direction should be set to be relatively large. May be.
- the number of cells to be searched may be set so that the number of cells to be searched in a direction in which the growth rate is high.
- the number of cells to be searched may be set so that the number of cells to be searched in the direction in which the migration speed is fast increases.
- the above is the method for identifying the cells surrounding the cell to be evaluated.
- the surrounding cells are automatically specified as described above.
- the user designates surrounding cells using the input device 5, and the cell evaluation unit 32 receives the designation information. You may make it identify the surrounding cell by accepting.
- the cell evaluation unit 32 sequentially specifies individual cells in the cell image as cells to be evaluated, sequentially specifies cells around the cells to be evaluated, and for each cell to be evaluated, The evaluation is confirmed using the evaluation results of the cells.
- the cell evaluation unit 32 of the present embodiment evaluates whether the cell to be evaluated is in a differentiated state or an undifferentiated state as described above. Specifically, in this embodiment, the degree of circularity of the cells to be evaluated and the surrounding cells is calculated, and when the degree of circularity is equal to or greater than a predetermined threshold, the undifferentiated state is evaluated and is less than the threshold. In some cases, the state is differentiated. Then, the evaluation results of the cell to be evaluated and the surrounding cells are stored together with the position information of the cell.
- whether the cell is in a differentiated state or an undifferentiated state may be evaluated based on image information of a predetermined region including the individual cell. .
- image information of a predetermined region including the individual cell For example, the density of cells in a predetermined area including cells to be evaluated is calculated, and if the density is equal to or higher than a predetermined threshold, it is evaluated as undifferentiated, and if it is lower than the threshold, the differentiated state You may make it evaluate that it is.
- a statistical value such as an average value, maximum value, or minimum value of luminance within a predetermined region including cells to be evaluated is calculated, and evaluation is performed in an undifferentiated state when the statistical value of luminance is less than a predetermined threshold value. However, if it is greater than or equal to the threshold value, it may be evaluated that it is in a differentiated state. Moreover, you may make it evaluate whether it is an undifferentiated state or a differentiation state by another well-known method.
- the cell evaluation unit 32 adds the evaluation results of the cells to be evaluated and the evaluation results of the surrounding cells, and when the number of cells evaluated to be in an undifferentiated state is larger, the cells to be evaluated Confirms the evaluation that it is in an undifferentiated state, and if the number of cells evaluated as a differentiated state is larger, the evaluation evaluates that the cell to be evaluated is in a differentiated state.
- one evaluation is performed by weighted addition of the evaluation result of the evaluation target cell and the evaluation result of the surrounding cells.
- a value may be calculated, and an evaluation result of a cell to be evaluated may be determined based on the evaluation value.
- the evaluation value when the evaluation result is in an undifferentiated state, the evaluation value is “2”. When the evaluation result is in a differentiated state, the evaluation value is “1”.
- the evaluation value of the cell is added to calculate one evaluation value, and when the evaluation value is equal to or greater than a predetermined threshold, the evaluation result of the cell to be evaluated is determined to be in an undifferentiated state and is less than the threshold In this case, the evaluation result of the cell to be evaluated may be determined as being in a differentiated state.
- the evaluation value of the evaluation target cell is weighted larger than the evaluation value of the surrounding cells and added. You may make it do.
- the evaluation values of the surrounding cells may be changed in weight according to the distance from the evaluation target cell. For example, a larger weight may be set for an evaluation value of a surrounding cell close to the cell to be evaluated.
- the evaluation value of the evaluation target cell and the evaluation value of the surrounding cells as described above, for example, when evaluating undifferentiation and differentiation of the cell based on the circularity, it is out of the normal range. For cells having an abnormal value of circularity, it may be determined that evaluation is impossible and the evaluation value may be set to “0”. By setting the evaluation value of a cell that cannot be evaluated in this way to “0”, the evaluation target cell can be evaluated using only the evaluation result of the cell that can be evaluated. It can be performed.
- examples where it is determined that a cell cannot be evaluated include, for example, a case where the cell is a dead cell, or a case where garbage that is not a cell is erroneously recognized as a cell.
- the evaluation value based on the brightness becomes an abnormal value and the evaluation is not possible. It may be determined that it is possible. This is caused by abnormal brightness of dead cells or dust. Since the nucleolus of dead cells is white, the brightness may be abnormally high, and the brightness of dust may also be abnormally high.
- the cell evaluation unit 32 sequentially specifies individual cells included in the cell image as evaluation target cells, and sequentially specifies surrounding cells for evaluation. At this time, the evaluation results that have already been stored may be used without evaluating the cells that have been evaluated once. As a result, the evaluation process can be simplified, and the processing speed can be increased.
- the cell evaluation unit 32 evaluates whether the cell to be evaluated is in an undifferentiated state or a differentiated state.
- the present invention is not limited to this, for example, a cell in which a cell group is induced to differentiate.
- the degree of differentiation of the cell may be evaluated.
- the stage of differentiation is expressed numerically based on the shape of individual cells, and statistical values such as the average, maximum, and minimum values of the degree of differentiation of the cells to be evaluated and the degree of differentiation of surrounding cells. And the statistical value may be determined as the degree of differentiation of the cell to be evaluated.
- weighted addition may be performed according to the distance between the cell to be evaluated and the surrounding cells.
- a cell group is a cancer cell, you may make it evaluate the malignancy of the cell.
- the display control unit 33 acquires the cell image read from the image acquisition unit 30, acquires the evaluation results of the individual cells evaluated by the cell evaluation unit 32, and displays them on the display 4.
- the evaluation results of cells specified by the user using the input device 5 may be displayed as text, or the evaluation results of individual cells may be displayed in different colors, for example.
- the cell evaluation image may be generated by mapping, and the cell evaluation image may be displayed superimposed on the cell image.
- the cell evaluation image may be a translucent image that allows observation through the cell image, or may be an image that represents the outline of each cell in different colors.
- the input device 5 includes a mouse, a keyboard, etc., and accepts setting input by the user.
- the input device 5 can accept setting inputs such as imaging conditions such as optical magnification of the phase-contrast microscope 20 and designation information of individual cells in the cell image.
- the culture to be photographed is selected from the plurality of accommodated culture containers by the transport unit 11, and the selected culture container is placed on the stage 10 (S10).
- an image of a cell colony in the culture vessel is captured by the phase contrast microscope 20 of the imaging device 2, and the captured cell image is acquired by the image acquisition unit 30 of the cell evaluation device 3 (S12).
- the boundary setting unit 31 sets a boundary in the cell image based on the state of the cell group in the cell image (S14). .
- the boundary between the differentiated area and the undifferentiated area is set.
- the boundary information set in the boundary setting unit 31 is output to the cell evaluation unit 32, and the cell evaluation unit 32 specifies individual cells in the cell image (S16). Subsequently, the cell evaluation unit 32 identifies surrounding cells based on the input boundary information (S18).
- the cell evaluation unit 32 sequentially specifies individual cells in the cell image as evaluation target cells, sequentially specifies the surrounding cells, and uses the evaluation result of the surrounding cells for the evaluation target cells. The evaluation is confirmed (S20).
- the evaluation results of the individual cell areas evaluated by the cell evaluation unit 32 are output to the display control unit 33, and the display control unit 33 displays the cell image and the evaluation results of the individual cells on the display 4 (S22).
- the cell culture observation system according to the first embodiment when the evaluation target cell is evaluated using the evaluation result of the surrounding cell, the evaluation target cell and the evaluation result of the surrounding cell cannot be evaluated. Although the cell evaluation result is not used, the cell culture observation system of the second embodiment is different from the cell image including the cell that cannot be evaluated when there is such a cell that cannot be evaluated. The cells that could not be evaluated were re-evaluated using the cell image captured in (1).
- the cell culture observation system of the second embodiment further includes an imaging condition acquisition unit 34 and an imaging control unit 35, as shown in FIG.
- the cell evaluation unit 32 in the cell culture observation system of the second embodiment evaluates the evaluation target cell using the evaluation result of the surrounding cells
- the cell evaluation unit 32 does not evaluate the evaluation target cell and the surrounding cells.
- identification information is added to the evaluation target area including the evaluation target cell and surrounding cells, and stored. This identification information is identification information indicating that the evaluation target area includes cells that cannot be evaluated.
- the imaging condition acquisition unit 34 sets the imaging condition for re-imaging the cell image used for re-evaluation of the evaluation target region. get.
- the imaging condition acquisition unit 34 acquires an optical magnification higher than the optical magnification when a cell image including cells that cannot be evaluated is captured. More specifically, for example, a cell image with an optical magnification of 4 times may be used for the first evaluation, and a cell image with an optical magnification of 20 times may be used for the re-evaluation. .
- the imaging conditions at the time of imaging the cell image containing the cell which cannot be evaluated it is memorize
- imaging conditions for re-imaging are also set in advance.
- the imaging condition acquisition unit 34 may acquire other imaging conditions other than the optical magnification described above.
- Other imaging conditions include, for example, an imaging region, imaging timing, exposure time of the imaging element, illumination light wavelength, observation light wavelength, and the like.
- the imaging area may be changed to a narrow range according to the change of the optical magnification at the time of re-imaging.
- the imaging timing for the re-imaging may be set when the culture is completed. Conversely, a past imaging timing may be acquired from an imaging timing at which a cell image including cells that cannot be evaluated is captured. That is, you may make it reevaluate using the cell image imaged in the past. Note that the imaging timing may be measured by providing a timer, for example. Further, it is desirable that the imaging timing is a timing that matches the cell division cycle.
- the exposure time of the image sensor when re-imaging is performed, the exposure time may be increased to increase the S / N of the cell image. In this case, the exposure time may be shortened to lower the brightness of the cell image.
- the resolution of the cell image may be increased by shortening the illumination light wavelength.
- the scattered light may be reduced and a cell image with less blur may be re-imaged.
- observation light wavelength may be switched by using, for example, a filter or a spectroscope at the time of re-imaging.
- the imaging condition for the re-imaging is set in advance for the imaging condition acquisition unit 34.
- the imaging condition acquisition unit 34 is not limited to this, and the evaluation target region includes cells that cannot be evaluated.
- the imaging condition may be automatically determined and acquired using the cell image.
- the imaging timing for example, the culture period is predicted from the density of individual cells in the cell image of the evaluation target region, and the imaging timing of re-imaging is based on a culture cycle set in advance with reference to the culture period. May be determined and acquired.
- the S / N of the cell image in the evaluation target area is acquired. If the S / N is equal to or less than a predetermined threshold, the exposure time is increased to increase the S / N of the cell image. Should be raised.
- statistical values such as the average value, maximum value, and minimum value of the brightness of the cell image in the evaluation target area are acquired, and when the statistical value is equal to or greater than a predetermined threshold, the exposure time is shortened to The brightness may be lowered.
- the resolution of the cell image in the evaluation target region is acquired, and if the resolution is not more than a predetermined threshold, the resolution of the cell image is increased by shortening the illumination light wavelength. That's fine.
- the blur of the cell image in the evaluation target region is acquired and the degree of blur is equal to or greater than a predetermined level, the blur of the cell image may be reduced by increasing the illumination light wavelength.
- the observation light wavelength may be changed by acquiring resolution and blur from the cell image.
- the imaging control unit 35 acquires the imaging conditions for re-imaging acquired by the imaging condition acquisition unit 34, and controls the imaging unit 2 of the imaging device 2 and the control unit 12 of the cell culture device 1 based on the imaging conditions. Output a signal.
- the control unit 29 of the imaging device 2 controls the optical magnification, the exposure time of the imaging element, the imaging timing, the illumination light wavelength, and the observation light wavelength based on the imaging control signal output from the imaging control unit 35.
- the control unit 12 of the cell culture device 1 controls the imaging region by moving the stage 10 based on the imaging control signal output from the imaging control unit 35.
- the individual cells in the cell image are specified and the surrounding cells are specified based on the input boundary information (S30 to S38). This is the same as the cell culture observation system of the first embodiment.
- the cell evaluation unit 32 sequentially specifies individual cells in the cell image as evaluation target cells, sequentially specifies the surrounding cells, and the evaluation result of the surrounding cells for each evaluation target cell. Is used to confirm the evaluation (S40). In this evaluation, if there are cells that cannot be evaluated among the cells to be evaluated and the surrounding cells (S42, NO), identification information is added to the evaluation target region at that time. Store (S44).
- the imaging condition acquisition unit 34 acquires imaging conditions for reimaging of the evaluation target area (S46).
- the imaging conditions acquired by the imaging condition acquisition unit 34 are output to the imaging control unit 35, and the imaging control unit 35 controls the control unit 29 of the imaging device 2 or the control unit of the cell culture device 1 based on the input imaging conditions. 12 outputs an imaging control signal. Then, re-imaging is performed under the control of the control unit 29 of the imaging device 2 or the control unit 12 of the cell culture device 1, and a cell image under an imaging condition different from the cell image used for the previous evaluation is acquired (S48). .
- the cell image acquired by re-imaging is input again to the cell evaluation unit 32, and re-evaluation is performed on the evaluation target region including cells that cannot be evaluated (S40).
- the evaluation results of the individual cell regions are output to the display control unit 33, and the display control unit 33 displays the cell image and the evaluation results of the individual cells. Is displayed on the display 4 (S50). Note that even when there are no cells that cannot be evaluated due to the above-described re-imaging, the process may be terminated by displaying a message or the like indicating that effect on the display 4.
- the cell culture observation system of the above embodiment when an individual cell is evaluated based on a cell image captured under a predetermined imaging condition, re-imaging is performed under a different imaging condition even when there are cells that cannot be evaluated. Since the re-evaluation is performed using the re-imaged cell image, individual cells can be evaluated with higher accuracy.
- the imaging condition acquisition unit 34 automatically acquires the imaging conditions.
- the present invention is not limited to this, and the user re-uses the input device 5 again.
- An imaging condition for imaging may be input, and the input imaging condition may be acquired by the imaging condition acquisition unit 34.
- the imaging control unit 35 automatically performs re-imaging based on the imaging conditions acquired by the imaging condition acquisition unit 34.
- the display control unit 33 displays the imaging conditions acquired by the imaging condition acquisition unit 34 on the display 4 and prompts the user to perform re-imaging so that the user manually performs re-imaging. Good.
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Abstract
Description
2 撮像装置
3 細胞評価装置
4 ディスプレイ
5 入力装置
10 ステージ
11 搬送部
12 制御部
15 培養容器
20 位相差顕微鏡
21 照明光源
22 スリット板
23 対物レンズ
24 位相差レンズ
25 対物レンズ
26 位相板
27 結像レンズ
28 撮像素子
29 制御部
30 画像取得部
31 境界設定部
32 細胞評価部
33 表示制御部
34 撮像条件取得部
35 撮像制御部
Claims (13)
- 細胞群を撮像した細胞画像を取得する画像取得部と、
前記細胞群における個々の細胞を認識し、該認識した個々の細胞のうちの評価対象の細胞と該評価対象の細胞の周囲の細胞とを特定し、前記周囲の細胞の評価結果と、前記評価対象の細胞の評価結果とに基づいて、前記評価対象の細胞の評価を確定する細胞評価部とを備えることを特徴とする細胞評価装置。 - 前記細胞評価部が、前記周囲の細胞の評価結果のうち、評価が可能な細胞の評価結果のみに基づいて、前記評価対象の細胞の評価を確定する請求項1記載の細胞評価装置。
- 前記細胞評価部が、前記評価対象の細胞の細胞核の大きさまたは形状、細胞質の大きさまたは形状、核小体の大きさまたは形状、前記細胞の増殖速度および遊走速度の少なくとも1つに基づいて、前記周囲の細胞を特定するための領域を決定し、該領域に全部または一部が含まれる細胞を周囲の細胞として特定する請求項1または2記載の細胞評価装置。
- 前記細胞評価部が、前記周囲の細胞を特定するための領域に存在する細胞の数が予め設定した数に到達するまで前記領域を広げる請求項3記載の細胞評価装置。
- 前記細胞評価部が、前記細胞画像の縦方向および横方向についてそれぞれ前記領域を広げる請求項4記載の細胞評価装置。
- 前記細胞評価部が、前記領域の前記縦方向および前記横方向のアスペクト比を決定する請求項5記載の細胞評価装置。
- 前記細胞評価部が、前記領域を広げる際、前記縦方向に探索する細胞数及び前記横方向に探索する細胞数を決定する請求項5記載の細胞評価装置。
- 前記細胞評価部が、前記評価対象の細胞と前記周囲の細胞との距離に基づいて、前記周囲の細胞の評価結果に対して重み付けを設定する請求項1から7いずれか1項記載の細胞評価装置。
- 前記細胞評価部が、前記評価対象の細胞の未分化状態または分化状態を評価する請求項1から8いずれか1項記載の細胞評価装置。
- 前記細胞評価部が、前記評価対象の細胞の分化度を評価する請求項1から8いずれか1項記載の細胞評価装置。
- 前記細胞群の状態に基づいて、前記細胞画像に境界を設定する境界設定部を備え、
前記細胞評価部が、前記周囲の細胞を特定する際、前記境界によって分割される複数の分割領域のうち前記評価対象の細胞が存在する分割領域内に存在する細胞のみを前記周囲の細胞として特定する請求項1から10いずれか1項記載の細胞評価装置。 - 細胞群を撮像した細胞画像を取得し、
前記細胞群における個々の細胞を認識し、該認識した個々の細胞のうちの評価対象の細胞と該評価対象の細胞の周囲の細胞とを特定し、前記周囲の細胞の評価結果と、前記評価対象の細胞の評価結果とに基づいて、前記評価対象の細胞の評価を確定することを特徴とする細胞評価方法。 - コンピュータを、細胞群を撮像した細胞画像を取得する画像取得部と、
前記細胞群における個々の細胞を認識し、該認識した個々の細胞のうちの評価対象の細胞と該評価対象の細胞の周囲の細胞とを特定し、前記周囲の細胞の評価結果と、前記評価対象の細胞の評価結果とに基づいて、前記評価対象の細胞の評価を確定する細胞評価部として機能させることを特徴とする細胞評価プログラム。
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EP3150692B1 (en) | 2018-11-28 |
US20170081628A1 (en) | 2017-03-23 |
EP3336171B1 (en) | 2023-08-09 |
EP3336171A1 (en) | 2018-06-20 |
EP3150692A1 (en) | 2017-04-05 |
JPWO2015182382A1 (ja) | 2017-04-20 |
JP6461128B2 (ja) | 2019-01-30 |
US10443029B2 (en) | 2019-10-15 |
EP3150692A4 (en) | 2017-08-16 |
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