  Purpose: To introduce and evaluate TrueLung, an automated pipeline for
computation and analysis of free-breathing and contrast-agent free pulmonary
functional MRI.
  Material and Methods: time-resolved ultra-fast bSSFP acquisitions are
transferred to TrueLung, which includes image quality checks, image
registration, and computation of perfusion and ventilation maps with matrix
pencil decomposition. Neural network whole-lung and lobar segmentations allow
quantification of impaired relative perfusion (RQ) and fractional ventilation
(RFV). TrueLung delivers functional maps and quantitative outcomes, reported
for clinicians in concise documents. We evaluated the pipeline in 75 cystic
fibrosis children. Whole-lung and lobar segmentations were manually refined
when necessary, and the impact on RQ and RFV was quantified.
  Results: Functional imaging was performed at 7.9 $\pm$ 1.8 (mean $\pm$ SD)
coronal slice positions per patient, totaling on average 6min 20s scan time per
patient. The whole pipeline required 20min calculation time per subject.
TrueLung delivered the functional maps of all the subjects for radiological
assessment. Quality controlling maps and segmentations lasted 1min 12s per
patient. The automated segmentations and quantification of whole-lung defects
were satisfying in 88% of patients (97% of slices) and the lobar quantification
in 73% (93% of slices). The segmentations refinements required 16s per patient
for the whole-lung, and 2min 10s for the lobe masks. The relative differences
in RFV and RQ between fully-automated and manually refined data were marginal.
  Conclusions: TrueLung quickly delivers functional maps and quantitative
outcomes in an objective and standardized way, suitable for radiological and
pneumological assessment with minimal manual input. TrueLung can be used for
clinical research in cystic fibrosis and might be applied across various lung
diseases.
