2. Image pre-processing with Nutil Transform
The Transform feature in the Nutil software enables image rotation, renaming, resising, and mirroring and is used to prepare image series for atlas alignment with QuickNII and segmentation with ilastik. It should be noted that QuickNII and ilastik have different input-image size requirements. In addition, it is important that the input images follow the standard naming convention described below.
The QuickNII and ilastik software have different input image size requirements. It is also important that the input images follow the prescribed naming convention.
Input requirements
For QuickNII, the input requirements are described in details in Puchades et al., 2019. To summarise, images should be in 24-bit PNG or JPEG format, with a resolution up to 16 megapixels (e.g., 4000x4000 or 5000x3000 pixels). Keep in mind that QuickNII does not benefit from image resolutions exceeding the resolution of the monitor in use. For a standard FullHD or widescreen display (1920x1080 or 1920x1200 pixels), the useful image area in QuickNII is approximately 1500x1000 pixels. Using a similar resolution ensures optimal image-loading performance.
For ilastik (Borg et al.2019), images are downscaled in order to enable efficient processing. The pixel classification algorithm relies on input from manual user annotations of the training images, and the features (intensity, edge, and/or texture) of the image pixels. The resising factor is determined by trial and error, with a test run performed with ilastik on images of different sizes to determine the optimal resolution for segmentation. As an example, in Yates et al., 2019, the images were downscaled by a factor of 10 for cellular features and by a factor of 20 for Alzheimer's plaques with respect to image width.
Naming convention
For QUINT analysis, Nutil Quantifier quantifies objects extracted from segmentations and registers them to regions defined by customised atlas maps. To match segmentations and corresponding atlas maps together, Nutil Quantifier relies on a unique ID in the file name of both files. The ID should be unique to the particular brain section and in the format sXXX, with XXX representing the section number. The section number should reflect the serial order and spacing of the sections (e.g., s002, s006, s010 for every 4th section starting with section 2).
Example: tg2345_MMSH_s001_segmentation.png
It is fine to include a string of letters and numbers followed by the unique ID.
Running the transformation
Consult the Nutil user online manual for the detailed procedure https://nutil.readthedocs.io/en/latest/