Automated scoring of regional lung perfusion in children from contrast enhanced 3D MRI

Tobias Heimann; Monika Eichinger; Grzegorz Bauman; Arved Bischoff; Michael Puderbach; Hans-Peter Meinzer

doi:10.1117/12.911946

23 February 2012 Automated scoring of regional lung perfusion in children from contrast enhanced 3D MRI

Tobias Heimann, Monika Eichinger, Grzegorz Bauman, Arved Bischoff, Michael Puderbach, Hans-Peter Meinzer

Proceedings Volume 8315, Medical Imaging 2012: Computer-Aided Diagnosis; 83150U (2012) https://doi.org/10.1117/12.911946
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

MRI perfusion images give information about regional lung function and can be used to detect pulmonary pathologies in cystic fibrosis (CF) children. However, manual assessment of the percentage of pathologic tissue in defined lung subvolumes features large inter- and intra-observer variation, making it difficult to determine disease progression consistently. We present an automated method to calculate a regional score for this purpose. First, lungs are located based on thresholding and morphological operations. Second, statistical shape models of left and right children's lungs are initialized at the determined locations and used to precisely segment morphological images. Segmentation results are transferred to perfusion maps and employed as masks to calculate perfusion statistics. An automated threshold to determine pathologic tissue is calculated and used to determine accurate regional scores. We evaluated the method on 10 MRI images and achieved an average surface distance of less than 1.5 mm compared to manual reference segmentations. Pathologic tissue was detected correctly in 9 cases. The approach seems suitable for detecting early signs of CF and monitoring response to therapy.

Citation Download Citation

Tobias Heimann, Monika Eichinger, Grzegorz Bauman, Arved Bischoff, Michael Puderbach, and Hans-Peter Meinzer "Automated scoring of regional lung perfusion in children from contrast enhanced 3D MRI", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83150U (23 February 2012); https://doi.org/10.1117/12.911946

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