AUTOMATIC SEGMENTATION OF NUCLEI IN 3D MICROSCOPY IMAGES OF C.ELEGANS

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A benchmark for comparison of cell tracking algorithms (2014, methodology): “After the ISBI 2013 workshop, the organizing committee confirmed the accuracy of the submitted results and compiled the final rankings presented in this article.”
Robust Nucleus/Cell Detection and Segmentation in Digital Pathology and Microscopy Images: A Comprehensive Review (2016, background): “step of nuclei segmentation [171], [172], [173], and further analysis is conducted to separate touching or overlapping nuclei.”
An automatic segmentation algorithm for 3D cell cluster splitting using volumetric confocal images (2011, methodology): “To solve this oversegmentation problem, postprocessing of merging is performed after watershed transformation (Najman & Schmitt, 1996; Adiga & Chaudhuri, 2001; Long et al. , 2007).”
Bioimage informatics: a new area of engineering biology (2008, methodology): “It is based on a series of bioimage-processing and mining techniques including C.elegans worm body straightening (Peng et al., 2008a), nuclei segmentation (Long et al., 2007c), annotation and cell identification (Long et al., 2008; Peng et al., 2008b) and atlas modeling.”