Apparatus and analytical evaluation methods using morphological feature parameters of a cell or cell population
The purpose of the present invention is to make it possible to efficiently generate information for cell analysis. A feature-group information generating unit generates, as feature-group information, information including values of N types of feature parameters (wherein N represents an integer having a value of 1 or more) about a morphological feature of a single cell of a plurality of cells or a morphological feature of a cell population based on data of one or more cell images included in a unit, the one or more cell images in the unit being selected from cell images capturing the cell population including the cells in accordance with a predetermined requirement. An analytical-model generating unit or an evaluation-target information acquiring unit acquires, as analyzing information for use in conducting predetermined cell analysis, information including values of M types (wherein M is an integer having a value independent of N) of parameters based on at least one of the N types of feature parameters included in the feature-group information.
1. An apparatus, comprising:
a central processing unit (CPU) and
a storage unit having stored thereon, a program comprising a set of instructions that, when executed by the CPU, configure the CPU to:
receive one or more first cell images capturing a cell population;
generate, based on the received one or more first cell images, feature-group information, including values of N types of feature parameters, each relating to a feature of a single cell of the cell population or a feature of multiple cells of the cell population, wherein
N represents an integer having a value of two or more, and
the N types of feature parameters include at least one first feature parameter relating to a feature of a single cell of the cell population and at least one second feature parameter relating to a feature of multiple cells of the cell population;
determine, based on at least one of the N types of feature parameters, analyzing information including first values of M types of parameters, wherein
M is an integer having a value of two or more and is independent of N, and
the M types of parameters include a subset of the N types of feature parameters and a supplementary parameter other than the N types of feature parameters in the feature-group information;
generate an analytical model for predicting cell quality using the analyzing information;
receive one or more second cell images capturing one or more cells to be analyzed;
perform an analysis of the one or more cells to be analyzed using the generated analytical model and second values for the M types of parameters determined based on the one or more second cell images; and
generate output information based on a comparison of the first values of the M types of parameters and the second values for the M types of parameters.
2. The apparatus according to claim 1 , wherein
determining the analyzing information is based on information about a distribution of the at least one second feature parameter relating to a feature of multiple cells of the cell population.
3. The apparatus according to claim 1 , wherein
the one or more first cell images includes at least two cell images captured at different time points, and
the analyzing information includes time information specifying a time point of capturing the one or more first cell images as one of the values of the M types of parameters.
4. A method of generating cell information, the method comprising:
receiving one or more first cell images capturing a cell population;
generating, based on the received one or more first cell images, feature-group information including values of N types of feature parameters, each relating to a feature of a single cell of the cell population or a feature of multiple cells of the cell population, wherein
N represents an integer having a value of two or more, and
the N types of feature parameters include at least one first feature parameter relating to a feature of a single cell of the cell population and at least one second feature parameter relating to a feature of multiple cells of the cell population;
determining, based on at least one of the N types of feature parameters, analyzing information including first values of M types of parameters, wherein
M is an integer having a value of two or more and is independent of N, and
the M types of parameters include a subset of the N types of feature parameters and a supplementary parameter other than the N types of feature parameters in the feature-group information;
generating an analytical model for predicting cell quality using the analyzing information;
receiving one or more second cell images capturing one or more cells to be analyzed;
performing an analysis of one or more cells to be analyzed using the generated analytical model and second values for the M types of parameters determined based on the one or more second cell images; and
generating output information based on a comparison of the first values of the M types of parameters and the second values for the M types of parameters.
5. A non-transitory computer readable medium having stored thereon, a plurality of instructions that, when executed by a central processing unit (CPU) configure the CPU to:
receive one or more first cell images capturing a cell population;
generate, based on the received one or more first cell images, feature-group information, including values of N types of feature parameters, each relating to a feature of a single cell of the cell population or a feature of multiple cells of the cell population, wherein
N represents an integer having a value of two or more, and
the N types of feature parameters include at least one first feature parameter relating to a feature of a single cell of the cell population and at least one second feature parameter relating to a feature of multiple cells of the cell population;
determine, based on at least one of the N types of feature parameters, analyzing information including first values of M types of parameters, wherein
M is an integer having a value of two or more and is independent of N, and
the M types of parameters include a subset of the N types of feature parameters and a supplementary parameter other than the N types of feature parameters in the feature-group information;
generate an analytical model for predicting cell quality using the analyzing information;
receive one or more second cell images capturing one or more cells to be analyzed;
perform an analysis of the one or more cells to be analyzed using the generated analytical model and second values for the M types of parameters determined based on the one or more second cell images; and
generate output information based on a comparison of the first values of the M types of parameters and the second values for the M types of parameters.