3D geometry-based quantification of colocalizations in multichannel 3D microscopy images of human soft tissue tumors.
We introduce a new model-based approach for automatic quantification of colocalizations in multichannel 3D microscopy images. The approach uses 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 the subcellular structures as well as to differentiate between different types of colocalizations. A statistical analysis was performed to assess the significance of the determined colocalizations. This approach was used to successfully analyze about 500 three-channel 3D microscopy images of human soft tissue tumors and controls.
Wörz
Stefan
S
Department Bioinformatics and Functional Genomics, Biomedical Computer Vision Group, University of Heidelberg, IPMB, BIOQUANT, and DKFZ Heidelberg, 69120 Heidelberg, Germany. s.woerz@dkfz.de
Sander
Petra
P
Pfannmöller
Martin
M
Rieker
Ralf J
RJ
Joos
Stefan
S
Mechtersheimer
Gunhild
G
Boukamp
Petra
P
Lichter
Peter
P
Rohr
Karl
K
D000465:Algorithms; D005456:Fluorescent Dyes / Q000737:chemistry; D042381:Granulocyte Precursor Cells / Q000166:cytology*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D007211:Indoles / Q000737:chemistry; D016018:Least-Squares Analysis; D018613:Microscopy, Confocal / Q000379:methods*; D008856:Microscopy, Fluorescence / Q000379:methods; D016011:Normal Distribution; D012983:Soft Tissue Neoplasms / Q000737:chemistry*; D016615:Telomere / Q000737:chemistry*
D005456:Fluorescent Dyes; D007211:Indoles; C007293:DAPI