IMAGE GENERATION SYSTEM, IMAGE GENERATION METHOD, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM
An image generation system comprising a computer processor that functions as: an image input part configured to input an input image, the input image being a time-series image obtained by imaging an observed cell over time; and an image generator configured to generate a growth prediction image of the observed cell from the time-series image of the observed cell based on a first learned model, which has learned a relationship between the time-series image of a learning cell and a feature of the learning cell, and output the growth prediction image as an output image.
1 . An image generation system comprising a computer processor that functions as:
an image input part configured to input an input image, the input image being a time-series image obtained by imaging an observed cell over time; and
an image generator configured to generate a growth prediction image of the observed cell from the time-series image of the observed cell based on a first learned model, which has learned a relationship between the time-series image of a learning cell and a feature of the learning cell, and output the growth prediction image as an output image.
2 . The image generation system according to claim 1 , wherein the image generator is configured to generate the growth prediction image of the observed cell corresponding to a designated feature.
3 . The image generation system according to claim 1 , wherein the observed cell contains a cell-derived colony.
4 . The image generation system according to claim 2 , wherein the feature is at least one of an elapsed culture time of the observed cell, a size of the observed cell, a color of the observed cell, a thickness of the observed cell, a transmittance of the observed cell, a fluorescence intensity of the observed cell, and a luminescence intensity of the observed cell.
5 . The image generation system according to claim 1 , wherein the time-series image is a time-lapse image.
6 . The image generation system according to claim 1 , further comprising:
an image determination part that generates image discrimination information such as a type and a state of the growth prediction image from the growth prediction image of the observed cell.
7 . An image generation method implemented in a computer system having a computer processor specifically programmed to perform the method, the method comprising:
an input process in which an input image is input, the input image being a time-series image obtained by imaging an observed cell over time; and
an image generation process in which a growth prediction image of the observed cell is generated from the time-series image of the observed cell based on a first learned model, which has learned a relationship between the time-series image of a learning cell and a feature of the learning cell, and the growth prediction image is output as an output image.
8 . The image generation method according to claim 7 , wherein, in the image generation step, the growth prediction image of the observed cell corresponding to the designated feature is generated.
9 . The image generation method according to claim 7 , wherein the observed cell contains cell-derived colonies.
10 . The image generation method according to claim 8 , wherein the feature is at least one of an elapsed culture time of the observed cell, a size of the observed cell, a color of the observed cell, a thickness of the observed cell, a transmittance of the observed cell, a fluorescence intensity of the observed cell, and a luminescence intensity of the observed cell.
11 . The image generation method according to claim 7 , wherein the time-series image is a time-lapse image.
12 . The image generation method according to claim 7 , further comprising:
an image discrimination information generation step in which image discrimination information such as a type and a state of the growth prediction image is generated from the growth prediction image of the observed cell.
13 . The image generation system according to claim 2 , wherein the growth prediction image includes a figure that predicts growth of a cell reflected in the input image.
14 . The image generation system according to claim 1 , comprising a display device configured to display the growth prediction image.
15 . The image generation system according to claim 1 , wherein the growth prediction image is a division prediction image that predicts the progress of cell division.
16 . The image generation system according to claim 1 , wherein the growth prediction image is a differentiation prediction image that predicts the differentiation process of a cell.
17 . The image generation system according to claim 4 , wherein
the input image is at least two or more time-series images corresponding to different culture elapsed times Tn (where n is a natural number),
the designated feature is an elapsed culture time of the observed cell, and
the designated feature is longer than T 1 having a shortest elapsed time among elapsed culture times of the two or more time-series images, and shorter than Tn which is one of the elapsed times (where T≠Tn).
18 . The image generation system according to claim 6 , wherein the image determination part is configured to
collect a plurality of growth prediction images having the same image discrimination information, and
output an image having the same image discrimination information of a plurality of observed cells, based on the plurality of growth prediction images.
19 . A non-transitory computer-readable medium with an executable program stored thereon, wherein the program instructs a processor to perform:
an input process in which a time-series image obtained by imaging an observed cell over time is input as an input image; and
an image generation process in which a growth prediction image of the observed cell is generated as an output image from the time-series image of the observed cell, based on a first learned model, which has learned about a relationship between the time-series image of a learning cell and a feature of the learning cell.