In general, an object can be identified based on size, shape, or color of the object. However, as in a case of white blood cells and cancer cells for example, when the objects have three-dimensional shapes, have sizes and shapes not significantly different from each other, and are colorless and transparent, the objects cannot be identified in an image obtained with a bright field microscope. Further, although a phase contrast microscope and a differential interference microscope are used for visualizing colorless and transparent cells, these microscopes lack quantitativity for optical thickness. In addition, depending on an objective lens used, these microscopes have a focus depth less than the thickness of a cell, and as a result, only two-dimensional information can be obtained in spite of the fact that the cell has a three-dimensional structure, and the object cannot be identified.
Cells which are released from an original tumor tissue or a metastatic tumor tissue and infiltrate into blood are called circulating tumor cells. The CTCs are present in a trace amount in the peripheral blood of solid cancer patients, are presumed to be associated with metastasis, and have been actively studied in recent years. On the other hand, it is important to identify white blood cells and cancer cells since most all of nucleated cells in the peripheral blood are white blood cells.
It has been reported that in a clinical application of circulating tumor cells, regarding breast cancer patients, when the number of circulating tumor cells in 7.5 mL of whole blood is less than 5, the one-year mortality is 19%, and when the number of circulating tumor cells is 5 or more, the one-year mortality is 53%. Accordingly, it is thought that identification and testing of circulating tumor cells are of great value in clinical applications, for example, are helpful for prognosis expectation.
In the invention disclosed in Patent Document 1, an image of a cell is acquired by an optical system for obtaining a bright field image, feature parameters (such as size, color information, and circularity) of the image are extracted, and the cell is identified based on the feature parameters. In addition, when identifying cells, a pattern recognition process is performed by using a neural network in that invention.