| scholarly article | Q13442814 |
| P50 | author | Göran Bergström | Q5573359 |
| P2093 | author name string | David Molnar | |
| Rauni Rossi Norrlund | |||
| Fredrik Kahl | |||
| Olof Enqvist | |||
| John Brandberg | |||
| Alexander Norlén | |||
| Jennifer Alvén | |||
| P2860 | cites work | Simultaneous truth and performance level estimation (STAPLE): an algorithm for the validation of image segmentation | Q34131486 |
| The Swedish CArdioPulmonary BioImage Study: objectives and design | Q36555278 | ||
| Epicardial and thoracic fat - Noninvasive measurement and clinical implications | Q37339297 | ||
| Multi-Atlas Segmentation with Joint Label Fusion. | Q37395662 | ||
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| Automated algorithm for atlas-based segmentation of the heart and pericardium from non-contrast CT. | Q42410887 | ||
| Automatic quantification of epicardial fat volume on non-enhanced cardiac CT scans using a multi-atlas segmentation approach | Q43602812 | ||
| Automated quantification of epicardial adipose tissue using CT angiography: evaluation of a prototype software. | Q46460430 | ||
| Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures. | Q50763709 | ||
| An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. | Q53593008 | ||
| A multicompartment body composition technique based on computerized tomography | Q72091066 | ||
| P433 | issue | 3 | |
| P921 | main subject | automation | Q184199 |
| P304 | page(s) | 034003 | |
| P577 | publication date | 2016-07-01 | |
| P1433 | published in | Journal of Medical Imaging | Q27725981 |
| P1476 | title | Automatic pericardium segmentation and quantification of epicardial fat from computed tomography angiography | |
| P478 | volume | 3 |
| Q89850542 | Artificial intelligence in medical imaging: A radiomic guide to precision phenotyping of cardiovascular disease |
| Q64237211 | CoreSlicer: a web toolkit for analytic morphomics |
| Q89559226 | Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT |
| Q89850384 | Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study |
| Q45945401 | Machine Learning Approaches in Cardiovascular Imaging. |
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