Journal article

Real-Time Respiratory Motion Analysis Using 4-D Shape Priors

Publication Details
Author(s): Wasza J, Fischer P, Leutheuser H, Oefner T, Bert C, Maier A, Hornegger J
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Publication year: 2016
Volume: 63
Journal issue: 3
Pages range: 485-495
ISSN: 0018-9294


Respiratory motion analysis based on range imaging (RI) has emerged as a popular means of generating respiration surrogates to guide motion management strategies in computer-assisted interventions. However, existing approaches employ heuristics, require substantial manual interaction, or yield highly redundant information. In this paper, we propose a framework that uses preprocedurally obtained 4-D shape priors from patient-specific breathing patterns to drive intraprocedural RI-based real-time respiratory motion analysis. As the first contribution, we present a shape motion model enabling an unsupervised decomposition of respiration induced high-dimensional body surface displacement fields into a low-dimensional representation encoding thoracic and abdominal breathing. Second, we propose a method designed for GPU architectures to quickly and robustly align our models to high-coverage multiview RI body surface data. With our fully automatic method, we obtain respiration surrogates yielding a Pearson correlation coefficient (PCC) of 0.98 with conventional surrogates based on manually selected regions on RI body surface data. Compared to impedance pneumography as a respiration signal that measures the change of lung volume, we obtain a PCC of 0.96. Using off-the-shelf hardware, our framework enables high temporal resolution respiration analysis at 50 Hz.

How to cite
APA: Wasza, J., Fischer, P., Leutheuser, H., Oefner, T., Bert, C., Maier, A., & Hornegger, J. (2016). Real-Time Respiratory Motion Analysis Using 4-D Shape Priors. IEEE Transactions on Biomedical Engineering, 63(3), 485-495.

MLA: Wasza, Jakob, et al. "Real-Time Respiratory Motion Analysis Using 4-D Shape Priors." IEEE Transactions on Biomedical Engineering 63.3 (2016): 485-495.

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