Reconstruction of Mammary Gland Structure Using Three-Dimensional Computer-Based Microscopy

Abstract

During the administrative funding period of this grant we have developed a system that permits three-dimensional reconstruction of entire the entire murine ductal epithelium from physical tissue sections. The system reduces the interaction required for low- resolution imaging of H&E stained sections, registration of images of consecutive sections and annotation of tissue structures -i.e. morphologically normal ducts and intraductal tumors- in the images. In addition, we have developed fully automatic tools for image registration and annotation that are now being integrated in our system and used in the reconstruction of the latest tissue specimens. Complementing morphological H&E based reconstruction, our system can be used for morphologically driven acquisition of high- resolution images form immunostained intermediate sections, both using fluorescence and bright field microscopy. To show the use of our system, we are using our it to compare the whole-gland distribution of hormone receptors (ER and PR) in the development of the mouse mammary gland. Under the one year, no cost extension requested, we will complete imaging and quantifying the whole-gland cell-by-cell ER and PR status of the mammary gland as it evolves through puberty into maturity.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2003
Accession Number
ADA420761

Entities

People

  • Carlos O. De Solorzano

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Biological Sciences
  • Breast Cancer
  • Carcinoma
  • Computational Science
  • Computer Programs
  • Computer Vision
  • Computers
  • Differential Equations
  • Graphical User Interface
  • High Resolution
  • Image Processing
  • Mammary Glands
  • Medical Personnel
  • Microscopy
  • Optics
  • Three Dimensional

Fields of Study

  • Medicine
  • Physics

Readers

  • Image Processing and Computer Vision.
  • Molecular Biology and Genetics
  • Oncology and Biomarker-Based Cancer Detection.