Features of daime
 
Batch import and processing. Series of images, which belong to the same experiment, or confocal z-stacks can be imported in a single step into daime. Subsequently, all images that belong to the same series or stack can be edited, segmented, analyzed, and visualized together. Thus, even hundreds of images can be handled with only a few mouse clicks. Of course, daime imports and analyzes single images, too.
Image segmentation. Once imported into daime, images can be prepared for segmentation (object recognition) for example by applying noise reduction and background removal algorithms. daime can automatically detect 2D and 3D objects in single images, image series, and confocal image stacks. The program offers various segmentation methods, which range from simple manual threshold selection to complex local thresholding and edge detection algorithms. An interactive object editor offers powerful tools to manually refine the results of automatic image segmentation. Features of individual objects (brightness, surface, area, volume, etc.) can be measured directly in the object editor. The objects in image series or confocal image stacks can also be measured automatically (batch processing).
Colour images and segmentation. When colour images have been imported into daime, the program offers an additional tool in the object editor for segmentation based on the colours of objects. This option can be extremely useful, for example to detect probe-labelled fluorescent cells in images with autofluorescent background, if the autofluorescence has a (slightly) different colour than the cells. Alternatively, the colour channels can be separated during image import and then be analyzed as independent images.
Abundance quantification of microorganisms. Research in microbial ecology often requires that the in situ abundance of microbial populations is quantified. daime greatly facilitates this tedious task by measuring the relative abundances (fractions of the total biovolume) of probe-labelled populations in digital images. This approach is not limited to single cells, but also works with cell aggregates that are embedded in biofilms.
Analysis of spatial localization patterns. The spatial arrangement of microorganisms, for example in biofilms and flocs, can reflect their biological interactions. Mutualistic symbionts may co-aggregate, whereas antagonists may rather avoid each other. Spatial localization cannot reliably be analyzed by simple microscopic observation, which lacks statistical support and bears the risk of overlooking subtle arrangement patterns. daime offers methods for quantifying the spatial localization of microbes in confocal images. By using these features, one can determine whether the spatial arrangement of probe-labelled microbial populations differs from a random distribution and whether the organisms do or do not co-aggregate.
Evaluation of rRNA-targeted probes. The specificity of rRNA-targeted oligonucleotide probes is greatly affected by the hybridization conditions (the stringency). To determine the optimal stringency for FISH with a new probe, one usually performs FISH experiments with probe-target and non-target organisms and increasing amounts of formamide in the hybridization buffers. daime can automatically evaluate such formamide series by measuring the brightness of the probe-labelled microbial cells in digital images. This feature yields a probe dissociation profile after only a few mouse clicks.

[click to enlarge]		 3D visualization. Confocal microscopy comes to life when combined with 3D visualization software. daime offers high-speed volume rendering engines designed to run on current commodity PCs and graphics hardware (including laptops). Rendering features include free rotation/zooming/panning/"fly-through" and popular visualization modes such as maximum intensity projection. daime also renders illuminated surfaces with shadows, can display semi-transparent surfaces, performs 3D clipping, and renders stereo anaglyphs at interactive frame rates. Showing the 3D arrangement of different biofilm populations is straightforward, because several confocal image stacks can easily be combined in the same 3D scene. Complex animations can be defined via a simple user interface and can be exported as image series for movie creation by third-party software.
The sample images show fluorescence-labelled biofilm microbes.

[click to enlarge]
[click to enlarge]