An Automated 3D Image-Processing Strategy for Small Animal Bioluminescence
Cancer Studies
Nikolai V. Slavine,
Roderick W. McColl, Edmond Richer, Ralph P. Mason and Peter P. Antich
Small-animal bioluminescence tomographic (BLT)
imaging can detect cellular or molecular events in vivo and
non-invasively. The specific goal of this project is to develop
and validate optimal methodologies for imaging light emission at
optical wavelengths in order to study small-animal tumors in vivo.
Our BLT System with multiple rotating, high sensitivity CCD
cameras offers imaging of bioluminescent light sources within
living animals and phantoms with appropriate spatial resolution.
To identify bioluminescence source location and strength we
use the surface light flux detected on the surface of imaged
object by CCD cameras. The quantitative 3D reconstruction of
bioluminescence sources can be strengthened by incorporation
of a priori knowledge on the small-animal anatomy and optical
properties. An important part of BLT is an automation of
image processing from the data acquisition to obtaining 3D
reconstructions. In order to optimize this procedure Linux based
software with multi-modality image handling environment was
developed in user-derived formats, such as Finite Element Meshes
or Color maps are also easily incorporated. Serial graphical
applications which operate in an object-oriented or data-driven
fashion are also available. A further objective of this work was to
develop and test a strategy behind automated methods for BLT
image processing to decrease the time of volumetric imaging and
quantitative assessment.
Index Terms
Bioluminescent imaging, 3D reconstruction, automation.
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