Auto-encoding of discriminating morphometry from cardiac mri.

AUTO-ENCODING OF DISCRIMINATING MORPHOMETRY FROM CARDIAC MRI. Proc IEEE Int Symp Biomed Imaging. 2014 Apr-May;2014:217-221 Authors: Ye DH, Desjardins B, Ferrari V, Metaxas D, Pohl KM Abstract We propose a fully-automatic morphometric encoding targeted towards differentiating diseased from healthy cardiac MRI. Existing encodings rely on accurate segmentations of each scan. Segmentation generally includes labour-intensive editing and increases the risk associated with intra- and inter-rater variability. Our morphometric framework only requires the segmentation of a template scan. This template is non-rigidly registered to the other scans. We then confine the resulting deformation maps to the regions outlined by the segmentations. We learn a manifold for each region and identify the most informative coordinates with respect to distinguishing diseased from healthy scans. Compared with volumetric measurements and a deformation-based score, this encoding is much more accurate in capturing morphometric patterns distinguishing healthy subjects from those with Tetralogy of Fallot, diastolic dysfunction, and hypertrophic cardiomyopathy. PMID: 28593032 [PubMed]
Source: Proceedings - International Symposium on Biomedical Imaging - Category: Radiology Tags: Proc IEEE Int Symp Biomed Imaging Source Type: research