AUTO-ENCODING OF DISCRIMINATING MORPHOMETRY FROM CARDIAC MRI.
AUTO-ENCODING OF DISCRIMINATING MORPHOMETRY FROM CARDIAC MRI.
复制标题
DOI：
10.1109/isbi.2014.6867848
复制
发表时间：
2014-04
期刊：
影响因子：
--
通讯作者：
Pohl KM
中科院分区：
文献类型：
--
作者：
Ye DH;Desjardins B;Ferrari V;Metaxas D;Pohl KM
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.
