The present invention relates generally to automated microscopy, and more specifically to improvements in the automatic detection of cell colonies' location on a glass sample slide. Additionally, the glass sample slide may be covered with a coverslip that protects cell colonies from contamination and damage. The coverslip area is that area of a specimen slide where most of focus mapping, image capture and image analysis needs to take place, because cell colonies reside underneath the coverslip. Thus the edges of the coverslip, which denote the area of interest for automated microscopy, need to be reliably detected.
At the present, operators typically scan and analyze the entire slide even though colonies of interest may reside only on several isolated spots within the slide. Operators are required to manually identify colonies (by drawing around them) resulting in slow system throughput. Furthermore, focus mapping can be slow or inaccurate due to sparse cell populations on colony slides.
Some existing methods attempt automated cell analysis of biological specimens by detecting candidate objects. Each slide is first scanned at a low microscope magnification. Candidate objects are identified based on their color, size, and shape; and their location is recorded. The candidate objects are then scanned with higher magnification lens. Thresholding and focusing steps are performed, followed by the morphological processing to identify candidate objects of interest by comparing optical features of the candidate object of interest to a target blob. However, those methods do not use morphological methods that enhance the image of the colonies of interest, neither do they associate the metaphases with the colonies. They also do not disclose a coverslip detection.
Some other existing methods create a composite image from smaller images. Subsequent image analysis is performed only over the areas of interest within the composite image. Those methods also eliminate the edges that were created by the overlaps or similar imperfections between the subimages caused by mechanical alignment errors. Substantially, those methods could be viewed as bandwidth saving methods. They do not disclose background subtraction, morphological methods for colony detection, thresholding, association of metaphases with the colonies, or the coverslip detection.
An accurate identification of the edges of a coverslip on a sample slide continues to be a challenge. Presently, detection methods typically scan and analyze the entire slide, i.e. the areas under and outside of the coverslip, which can be inefficient and time-consuming. Or to reduce scan and analysis time the operators need to accurately place the coverslip in the same position on each slide so that a fixed scan area is applicable to all slides.
Some methods for detecting a microscope slide coverslip are known. For example, these methods can detect the coverslip by locating all four coverslip edges when those edges satisfy a set of predetermined criteria. However, those methods are rule-based and time consuming, and are not applicable to detecting a coverslip of unknown size and location.
Yet some other methods use non-linear Hough transforms to detect some features of the cell or objects within the cell (e.g., detecting nucleus centre, plasma membrane, etc.). Those methods also use an adjustment of the pixel intensity level to improve feature accuracy, presumably on the suspect edges of the objects of interest. However, those methods detect a presence of the objects within the cell, but not their precise outline, nor do they detect the edges of the coverslip.
Some other methods detect objects that are similarly shaped using a pre-existing shape library or they detect a grid-like arranged specimens on a slide using Hough transformation. The centroids of the specimen are detected using 2D peak detection algorithms. Column and row orientations are detected followed by the calculation of the overall grid intersection locations. The method can identify the specimens by finding their expected location in the 2D grid. However, those methods do not detect edges of the object (i.e. coverslip edges), neither do they perform any image enhancements, such as, for example, dark field subtraction.
There is therefore a need for systems and methods that accurately and automatically detect the location of the coverslip on a microscope slide as well as the location of cell colonies of interest underneath the coverslip.