Open AccessEfficient, interactive, and three‐dimensional segmentation of cell nuclei in thick tissue sections
Author(s) -
Lockett Stephen J.,
Sudar Damir,
Thompson Curtis T.,
Pinkel Dan,
Gray Joe W.
Publication year - 1998
Publication title -
cytometry
Language(s) - English
Resource type - Journals
eISSN - 1097-0320
pISSN - 0196-4763
DOI - 10.1002/(sici)1097-0320(19980401)31:4<275::aid-cyto7>3.0.co;2-i
Subject(s) - segmentation , computer science , nucleus , artificial intelligence , surface (topology) , computer vision , pattern recognition (psychology) , algorithm , biology , mathematics , geometry , neuroscience
Segmentation of intact cell nuclei in three‐dimensional (3D) images of thick tissue sections is an important basic capability necessary for many biological research studies. Because automatic algorithms do not correctly segment all nuclei in tissue sections, interactive algorithms may be preferable for some applications. Existing interactive segmentation algorithms require the analyst to draw a border around the nucleus under consideration in all successive two‐dimensional (2D) planes of the 3D image. The present paper describes an algorithm with two main advantages over the existing method. First, the analyst draws borders only in 2D planes that cut approximately through the center of the nucleus under consideration so that the nuclear borders generally are most distinct. Second, the analyst draws only five borders around each nucleus, and then the algorithm interpolates the entire surface. The algorithm results in segmented objects that correspond to individual, visually identifiable nuclei. The segmented surfaces, however, may not exactly represent the true nuclear surface. An optional, automatic surface optimization algorithm can be applied to reduce this error. Cytometry 31:275–286, 1998. © 1998 Wiley‐Liss, Inc.