Publication Classification:

Segmentation Evaluation = Object-level evaluation

Data Axes = X-Y-Z

• "Bajcsy P, Lee S-C, Lin a, Folberg R: Three-dimensional volume reconstruction of extracellular matrix proteins in uveal melanoma from fluorescent confocal laser scanning microscope images. J Microsc 2006, 221(Pt 1):30–45."

• "Indhumathi C, Cai YY, Guan YQ, Opas M: An automatic segmentation algorithm for 3D cell cluster splitting using volumetric confocal images. J Microsc 2011, 243:60–76."

• "Lin G, Adiga U, Olson K, Guzowski JF, Barnes C a, Roysam B: A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks. Cytometry A 2003, 56:23–36."

• "Lin G, Chawla MK, Olson K, Barnes CA, Guzowski JF, Bjornsson C, Shain W, Roysam B: A multi-model approach to simultaneous segmentation and classification of heterogeneous populations of cell nuclei in 3D confocal microscope images. Cytom Part A 2007, 71:724–736."

• "Lou X, Kang M, Xenopoulos P, Muñoz-Descalzo S, Hadjantonakis A-K: A Rapid and Efficient 2D/3D Nuclear Segmentation Method for Analysis of Early Mouse Embryo and Stem Cell Image Data. Stem cell reports 2014, 2:382–97."

• "Wählby, C.; Sintorn, I.-M.; Erlandsson, F.; Borgefors, G.; Bengtsson, E.: Combining intensity , edge and shape information for 2D and 3D segmentation of cell nuclei in tissue sections. J Microsc 2004, 215(January):67–76."

• "Zhu Y, Olson E, Subramanian A, Feiglin D, Varshney PK, Krol A: Neuronal nuclei localization in 3D using level set and watershed segmentation from laser scanning microscopy images. In Proc. SPIE. Volume 6914. Edited by Reinhardt JM, Pluim JPW.; 2008:691441–691441–8."

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The National Institute of Standards and Technology (NIST) uses substantial efforts to select publications that meet the publication survey criteria. However, NIST makes no warranties that the survey is exhaustive. The survey and its contents are provided by NIST as a public service and are strictly provided "AS IS" with no warranties of any type. Furthermore, NIST does not make any statements about quality of publications by including them in the survey classification and does not imply any recommendation or endorsement.