DeTEC: Detection of Touching Elongated Cells in SEM Images

Ali Memariani, Christophoros Nikou, Bradley T. Endres, Eugénie Bassères, Kevin W. Garey, Ioannis A. Kakadiaris

Abstract: A probabilistic framework using two random fields, DeTEC (Detection of Touching Elongated Cells) is proposed to detect cells in scanning electron microscopy images with inhomogeneous illumination. The first random field provides a binary segmentation of the image to superpixels that are candidates belonging to cells, and to superpixels that are part of the background, by imposing a prior on the smoothness of the texture features. The second random field selects the superpixels whose boundaries are more likely to form elongated cell walls by imposing a smoothness prior onto the orientations of the boundaries. The method is evaluated on a dataset of Clostridium difficile cell images and is compared to CellDetect.