Related Experiment Video
Updated: Jun 13, 2026

Phase-Resolved Functional Lung MRI for Pulmonary Ventilation and Perfusion (V/Q) Assessment
Published on: August 9, 2024
Exploiting quasiperiodicity in motion correction of free-breathing myocardial perfusion MRI
Gert Wollny1, Maria J Ledesma-Carbayo, Peter Kellman
1Group of Biomedical Imaging Technologies, Department of Electronic Engineering, ETSI Telecomunicacion, Universidad Politechnica de Madrid, 28040 Madrid, Spain. gert@die.upm.es
Abstract:
Free-breathing image acquisition is desirable in first-pass gadolinium- enhanced magnetic resonance imaging (MRI), but the breathing movements hinder the direct automatic analysis of the myocardial perfusion and qualitative readout by visual tracking. Nonrigid registration can be used to compensate for these movements but needs to deal with local contrast and intensity changes with time. We propose an automatic registration scheme that exploits the quasiperiodicity of free breathing to decouple movement from intensity change. First, we identify and register a subset of the images corresponding to the same phase of the breathing cycle. This registration step deals with small differences caused by movement but maintains the full range of intensity change. The remaining images are then registered to synthetic references that are created as a linear combination of images belonging to the already registered subset. Because of the quasiperiodic respiratory movement, the subset images are distributed evenly over time and, therefore, the synthetic references exhibit intensities similar to their corresponding unregistered images. Thus, this second registration step needs to account only for the movement. Validation experiments were performed on data obtained from six patients, three slices per patient, and the automatically obtained perfusion profiles were compared with profiles obtained by manually segmenting the myocardium. The results show that our automatic approach is well suited to compensate for the free-breathing movement and that it achieves a significant improvement in the average Pearson correlation coefficient between manually and automatically obtained perfusion profiles before (0.87 +/- 0.18) and after (0.96 +/- 0.09) registration.
More Related Videos
08:35Oxygenation-sensitive Cardiac MRI with Vasoactive Breathing Maneuvers for the Non-invasive Assessment of Coronary Microvascular Dysfunction
Published on: August 17, 2022
06:56Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
Published on: January 7, 2021