Computational Approaches for the Processing of Cerebral Histological Images of Small Animals

Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 120)

Abstract

Histological sections of tissue have been studied for many decades and constitute one the most prevalent means of information on biological processes and functions for animals. With the introduction of digital images in medicine, image processing techniques derived from medical imaging were adapted to scanned histological sections in order to improve their visualization and analysis. More recently, the introduction of virtual microscopy yet increased the interest of analyzing histological sections on a computer screen and opened up a whole branch of biomedical image processing dedicated to the extraction of information contained in histological sections at very high magnification. In this work we present three novel approaches to study histological sections of the brain in small animals: 1) the alignment of histological sections to create a 3D image, 2) the processing of very large microscopy sections and 3) the correlation of histological sections with 3D in vivo images acquired on medical imaging devices.

Keywords

Histological Section Large Image Black Reaction Virtual Microscopy Symmetrical Region 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.CEA-CNRS, MIRCenFontenay-aux-RosesFrance

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