Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix joint fusion bugs multi modal data #1302

Merged
merged 2 commits into from
Feb 5, 2022
Merged

Fix joint fusion bugs multi modal data #1302

merged 2 commits into from
Feb 5, 2022

Commits on Feb 5, 2022

  1. BUG: Multi-modal atlas data causes duplicate atlases 

    For multiple modality images, the atlases were incorrectly
doubled.

For example, 3 atlases with T1 & T2 modalities should result in
a list of lists like

0: [A1-T1, A1-T2]
1: [A2-T1, A2-T2]
2: [A3-T1, A3-T2]

but instead resulted in

0: [A1-T1, A1-T2]
1: [A1-T1, A1-T2]
2: [A2-T1, A2-T2]
3: [A2-T1, A2-T2]
4: [A3-T1, A3-T2]
5: [A3-T1, A3-T2]

Only the first 3 elements are processed, so about 1/2
the atlases are not used.
    @hjmjohnson
    hjmjohnson committed Feb 5, 2022
    Configuration menu
    Copy the full SHA
    653f13e View commit details
    Browse the repository at this point in the history

  2. BUG: MSE requires both images are scaled similarly 

    Scaling the target, but not the atlases results in invalid
MSE minimized results when searching local regions.

TARGET[i] = [ 1, 1, 1, 1]
NORMALIZED_TARGET[i]=[ 0, 0, 0 ,0]

ATLAS[i]  = [ 1, 1, 1, 1]
ATLAS[i+1]= [ 0, 1, 1, 1]

MSE (NORMALIZED_TARGET[i], ATLAS[i])   = 4
MSE (NORMALIZED_TARGET[i], ATLAS[i+1]) = 3
    @hjmjohnson
    hjmjohnson committed Feb 5, 2022
    Configuration menu
    Copy the full SHA
    2d85646 View commit details
    Browse the repository at this point in the history