Table 1.
Similarities and differences between detectCilia, ACDC, and CiliaQ.
| Feature | detectCilia | ACDC | CiliaQ |
|---|---|---|---|
| Detection mode | Automatic | Manual or automatic with possibility for manual corrections | Automatic with possibility for manual corrections |
| Valid image dimensions | 2D, 3D | 2D | 2D, 3D, 4D (= 3D + time) |
| Data input format | CZI, TIF | TIF, JPEG | All common formats (using the Bio-Formats plugin for ImageJ) |
| Skeletonization of cilia | No | Yes | Yes |
| z-stack projection method | Maximum (as default) or mean intensity | — | Maximum intensity |
| Segmentation parameter values | Automatically or manually set | Manually and automatically set a | Automatically set with the choice of different segmentation methods |
| Filter parameter values | Automatically set | Manually set | Manually set |
| Cell count (stained nuclei) | Yes | Yes b | No |
| Programming language | R | MATLAB | Java |
| Graphical user interface | No | Yes | Yes |
| Open-source | Yes | No | Yes |
| Reproducible image analysis | Yes | Yes c | Yes c |
a
After manually labeling a representative image, the post-processing parameter values may be chosen automatically by an optimization algorithm.
b
The cell count did not work correctly in our case.
c
Only if no manual corrections are made and all used parameter values are published.