Automatic segmentation of histological structures in mammary gland tissue sections

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Real-time three-dimensional (3D) reconstruction of epithelial structures in human mammary gland tissue blocks mapped with selected markers would be an extremely helpful tool for breast cancer diagnosis and treatment planning. Besides its clear clinical application, this tool could also shed a great deal of light on the molecular basis of breast cancer initiation and progression. In this paper we present a framework for real-time segmentation of epithelial structures in two-dimensional (2D) images of sections of normal and neoplastic mammary gland tissue blocks. Complete 3D rendering of the tissue can then be done by surface rendering of the structures detected in ... continued below

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Fernandez-Gonzalez, Rodrigo; Deschamps, Thomas; Idica, Adam K.; Malladi, Ravikanth & Ortiz de Solorzano, Carlos February 17, 2004.

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Real-time three-dimensional (3D) reconstruction of epithelial structures in human mammary gland tissue blocks mapped with selected markers would be an extremely helpful tool for breast cancer diagnosis and treatment planning. Besides its clear clinical application, this tool could also shed a great deal of light on the molecular basis of breast cancer initiation and progression. In this paper we present a framework for real-time segmentation of epithelial structures in two-dimensional (2D) images of sections of normal and neoplastic mammary gland tissue blocks. Complete 3D rendering of the tissue can then be done by surface rendering of the structures detected in consecutive sections of the blocks. Paraffin embedded or frozen tissue blocks are first sliced, and sections are stained with Hematoxylin and Eosin. The sections are then imaged using conventional bright field microscopy and their background is corrected using a phantom image. We then use the Fast-Marching algorithm to roughly extract the contours of the different morphological structures in the images. The result is then refined with the Level-Set method which converges to an accurate (sub-pixel) solution for the segmentation problem. Finally, our system stacks together the 2D results obtained in order to reconstruct a 3D representation of the entire tissue block under study. Our method is illustrated with results from the segmentation of human and mouse mammary gland tissue samples.

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  • Journal Name: Journal of Biomedical Optics; Journal Volume: 9; Journal Issue: 3

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  • Report No.: LBNL--53241
  • Grant Number: AC03-76SF00098
  • DOI: 10.1117/1.1699011 | External Link
  • Office of Scientific & Technical Information Report Number: 838539
  • Archival Resource Key: ark:/67531/metadc782110

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Office of Scientific and Technical Information (OSTI) is the Department of Energy (DOE) office that collects, preserves, and disseminates DOE-sponsored research and development (R&D) results that are the outcomes of R&D projects or other funded activities at DOE labs and facilities nationwide and grantees at universities and other institutions.

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  • February 17, 2004

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  • Dec. 3, 2015, 9:30 a.m.

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  • April 4, 2016, 12:19 p.m.

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Fernandez-Gonzalez, Rodrigo; Deschamps, Thomas; Idica, Adam K.; Malladi, Ravikanth & Ortiz de Solorzano, Carlos. Automatic segmentation of histological structures in mammary gland tissue sections, article, February 17, 2004; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc782110/: accessed August 18, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.