Paper
9 March 2010 3D geometry-based quantification of colocalizations in three-channel 3D microscopy images of soft tissue tumors
Stefan Wörz, Petra Sander, Martin Pfannmöller, Ralf J. Rieker, Stefan Joos, Gunhild Mechtersheimer, Petra Boukamp, Peter Lichter, Karl Rohr
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Abstract
We introduce a new model-based approach for automatic quantification of colocalizations in multi-channel 3D microscopy images. The approach is based on different 3D parametric intensity models in conjunction with a model fitting scheme to localize and quantify subcellular structures with high accuracy. The central idea is to determine colocalizations between different channels based on the estimated geometry of subcellular structures as well as to differentiate between different types of colocalizations. Furthermore, we perform a statistical analysis to assess the significance of the determined colocalizations. We have successfully applied our approach to about 400 three-channel 3D microscopy images of human soft-tissue tumors.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stefan Wörz, Petra Sander, Martin Pfannmöller, Ralf J. Rieker, Stefan Joos, Gunhild Mechtersheimer, Petra Boukamp, Peter Lichter, and Karl Rohr "3D geometry-based quantification of colocalizations in three-channel 3D microscopy images of soft tissue tumors", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 762616 (9 March 2010); https://doi.org/10.1117/12.843772
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Cited by 1 scholarly publication.
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KEYWORDS
3D modeling

Image segmentation

3D image processing

Statistical analysis

Microscopy

Tumors

Tissues

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