Joint 3D Cell Segmentation and Classification in the Arabidopsis Root using Energy Minimization and Shape Priors
IEEE International Symposium on Biomedical Imaging (ISBI): 422--425, 2013
Abstract: This paper presents a discrete energy minimization approach to integrate different prior knowledge and image cues for
simultaneous cell segmentation and classification. When there are multiple types of cells to segment, the segmentation
of cells and the classification of the cell types are dependent on each other. The presented approach selects the
optimal segmentations from hypotheses and infers the cell types in the same process. The approach is applied to the
volumetric data of Arabidopsis roots.
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@InProceedings{LSR13a, author = "K. Liu and T. Schmidt and T. Blein and J. D{\"u}rr and K.Palme and O. Ronneberger", title = "Joint 3D Cell Segmentation and Classification in the Arabidopsis Root using Energy Minimization and Shape Priors", booktitle = "IEEE International Symposium on Biomedical Imaging (ISBI)", pages = "422--425", year = "2013", url = "http://lmbweb.informatik.uni-freiburg.de/Publications/2013/LSR13a" }