As scientists we need to talk about specific spatial things
It takes a lot of time, potentially (manual vs. automated)
It is subjective (if manual)
It can really change analysis outcomes
De-identification of people's faces is important
To reduce multiple comparisons, if you have a priori hypotheses, that is useful and so you need to implement these hypotheses
The brain consists of multiple tissue types/stuff, so we obviously need to accurately select the part of the data we care about
Issue: criterion for success is currently not objective and subjective (and therefore somewhat of an "art"/"craft"). Eyeballs are important. Expertise is important.
If a newbie is doing manual segmentation, they might get it completely wrong?!! (So there is a risk of making things even worse!) Can even happen for non-newbies.
Issues/gripes/challenges:
Takes forever
Not clear how to interpret noisy functional measures
Risk of people suspecting you doing something dirty
People disagreeing on what is right
This is thankless work, unfortunately. (So, choose your battles.)
ROI formats:
Binary values (0 means not in, 1 means in)
Integer values (1–N indicate N different regions)
Volumes are a lot more straightforward (just a 3D grid); surfaces are a lot harder and generally clunkier to work with.
General "tools" and "methods" for dealing with ROIs:
Click and automatically determine all "connected" voxels
Post-ROI 'morphological' operations: dilate, erode, union, intersection, smoothing, and other arithmetic operations
Experts will know how to interplay manual clicking and automatic morphological operations
Trackpad vs. mouse vs. tablets
Thresholding operations (e.g. value > 10)
Magical smoothing/filtering/operations to "clean up" the data prior to you clicking on it
Adjust the contrast/intensity for the specific part of the volume that you are staring at
Make sure to look at ALL 3 views to really understand the geometry of the structure. If your current slice is almost parallel to the structure, the visual may look weird.
Check your work. The eyeballs are always right.
Various types (scenarios):
T1 segmentation (e.g. for surfaces)
Defining a brain region from functional data
Anatomical segmentation, e.g. vessels
Atlas parcellations can deliver you ROIs
Identification of subcortical areas from anatomy (REALLY HARD)
Brain extraction from T1s (getting rid of face / skull)
Quick-and-dirty 3D ellipse to define on a volume
Principles/ideas that guide how you proceed:
Partial voluming - your single voxels might mix two different tissue types, due to limited resolution
Thermal noise - the data may be noisy
Bias field - there may be low-frequency changes in intensity across the volume.
One strategy is to correct the bias field before segmenting...
For functional data, consider looking both with and without thresholding
Be careful of 'kissing' gray matter (nearby in 3D space might be far away in cortical space)