An image processing apparatus comprising: nucleus candidate area extracting means for extracting a circumscribed rectangular area of pixel clusters in a captured image of target cells as a nucleus candidate area; cell-size estimating unit for estimating a rectangular area of a cell size; defining means for defining a cell rectangular area as a cell candidate area on the basis of the nucleus candidate area, wherein a point of the nucleus candidate area is located at the center of the cell candidate area having the estimated rectangular area; feature value extracting means for extracting an image feature value of an image of a cell candidate area in the captured image; discriminating means for using a pre-trained discriminator to identify whether or not a target cell is shown in the cell candidate area, on the basis of the image feature value of the image of the cell candidate area; display means for, when the cell candidate area is identified as an area in which the target cell is shown, displaying the image of the cell candidate area; characterised by accepting means for, when the cell candidate area is identified as an area in which the target cell is shown, accepting a user input from a user about whether or not the target cell is shown in the cell candidate area; discriminator training means for, when the cell candidate area is identified as an area in which the target cell is shown, training the discriminator by using an updated image feature value of the image of the cell candidate area as a training sample on the basis of the user input accepted by the accepting means; and updating means for, when the user determines that the target cell is shown in the cell candidate area, specifying an outline area corresponding to a cell wall and updating the cell rectangular area of the cell candidate area by circumscribing an updated cell rectangular area on the basis of the specified outline area, the outline area being included in the cell candidate area, wherein the discriminator training means trains the discriminator by using an image feature value of an image in the updated cell rectangular area of the cell candidate area as the updated image feature value. nucleus candidate area extracting means for extracting a circumscribed rectangular area of pixel clusters in a captured image of target cells as a nucleus candidate area; cell-size estimating unit for estimating a rectangular area of a cell size; defining means for defining a cell rectangular area as a cell candidate area on the basis of the nucleus candidate area, wherein a point of the nucleus candidate area is located at the center of the cell candidate area having the estimated rectangular area; feature value extracting means for extracting an image feature value of an image of a cell candidate area in the captured image; discriminating means for using a pre-trained discriminator to identify whether or not a target cell is shown in the cell candidate area, on the basis of the image feature value of the image of the cell candidate area; display means for, when the cell candidate area is identified as an area in which the target cell is shown, displaying the image of the cell candidate area; characterised by accepting means for, when the cell candidate area is identified as an area in which the target cell is shown, accepting a user input from a user about whether or not the target cell is shown in the cell candidate area; discriminator training means for, when the cell candidate area is identified as an area in which the target cell is shown, training the discriminator by using an updated image feature value of the image of the cell candidate area as a training sample on the basis of the user input accepted by the accepting means; and updating means for, when the user determines that the target cell is shown in the cell candidate area, specifying an outline area corresponding to a cell wall and updating the cell rectangular area of the cell candidate area by circumscribing an updated cell rectangular area on the basis of the specified outline area, the outline area being included in the cell candidate area, wherein the discriminator training means trains the discriminator by using an image feature value of an image in the updated cell rectangular area of the cell candidate area as the updated image feature value.