Learn2Reg 2021, LungCT, validation

TRE: distance between matching landmarks. rTRE: the TRE over the length of the image's diagonal, to compare datasets of other sizes and units. SDlogJ: how irregular the deformation is, 0 is perfectly smooth. Folds: share of the image where the deformation folds over itself.

Scored the way the challenge scores

The same results with the Learn2Reg 2021, LungCT challenge's own measures, on its validation pairs: mean ± standard deviation.

What the challenge published

On the challenge's test set: other pairs than the ones above, and entries trained or tuned for the task. It shows the level of the challenge; these are not results of this benchmark.

Source: Hering et al., Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning, IEEE TMI 2023, Table VIII.

Click a score to look at that result: the fixed image, and over it the moving image after registration, with the annotations. Underlined scores have their image; for the others you see the pair without the result. A green cell gained against no registration on that pair, a red one lost.

About the data

The first test caseClick to look at every case.

Test pairs

The task's 3 official validation pairs are the test cases. The 10 development pairs come from its training pairs 0004 to 0020, scored on its official corrField keypoints (fixed_keypoints.csv), since its manual landmarks are public for the validation pairs only.

Truth

landmarks by experts the challenge's public points

Source

learn2reg.grand-challenge.org
github.com/MDL-UzL/L2R

Licence

CC BY 4.0