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Since manual object detection is very inaccurate and time consuming, someautomatic object detection tools have been developed in recent years. At themoment, there is no image analysis software available which provides anautomatic, objective assessment of 3D foci which is generally applicable.Complications arise from discrete foci which are very close or even come incontact to other foci, moreover they are of variable sizes and show variablesignal-to-noise, and must be analyzed fully in 3D. Therefore we introduce the3D-OSCOS (3D-Object Segmentation and Colocalization Analysis based on Spatialstatistics) algorithm which is implemented as a user-friendly toolbox forinteractive detection of 3D objects and visualization of labeled images.

Automatic 3D object detection of Proteins in Fluorescent labeled microscope images with spatial statistical analysis