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DETCIC: Detection of Elongated Touching Cells with Inhomogeneous Illumination using a Stack of Conditional Random Fields

Automated detection of touching cells in images with inhomogeneous illumination is a challenging problem. A detection framework using a stack of two conditional random fields is proposed to detect touching elongated cells in scanning electron microscopy images with inhomogeneous illumination. The first conditional random field employs shading information to segment the cells where the effect of inhomogeneous illumination is reduced. The second conditional random field estimates the cell walls using their estimated cell wall probability. The method is evaluated using a dataset of Clostridium difficile cells. Finally, the method is compared with two region-based cell detection methods, CellDetect and DeTEC, improving the F-score by at least 20%.