title: Automatic view planning for cardiac MRI acquisition.
abstract: Conventional cardiac MRI acquisition involves a multi-step approach, requiring a few double-oblique localizers in order to locate the heart and prescribe long- and short-axis views of the heart. This approach is operator-dependent and time-consuming. We propose a new approach to automating and accelerating the acquisition process to improve the clinical workflow. We capture a highly accelerated static 3D full-chest volume through parallel imaging within one breath-hold. The left ventricle is localized and segmented, including left ventricle outflow tract. A number of cardiac landmarks are then detected to anchor the cardiac chambers and calculate standard 2-, 3-, and 4-chamber long-axis views along with a short-axis stack. Learning-based algorithms are applied to anatomy segmentation and anchor detection. The proposed algorithm is evaluated on 173 localizer acquisitions. The entire view planning is fully automatic and takes less than 10 seconds in our experiments.
authors: Image Analytics and Informatics, Siemens Corporate Research, Princeton, NJ, USA. xiaoguang.lu@siemens.com
authors: Xiaoguang
authors: X
authors: Lu
authors: Marie-Pierre
authors: MP
authors: Jolly
authors: Bogdan
authors: B
authors: Georgescu
authors: Carmel
authors: C
authors: Haye
authors: Peter
authors: P
authors: Speier
authors: Michaela
authors: M
authors: Schmidt
authors: Xiaoming
authors: X
authors: Bi
authors: Randall
authors: R
authors: Kroeker
authors: Dorin
authors: D
authors: Comaniciu
authors: Peter
authors: P
authors: Kellman
authors: Edgar
authors: E
authors: Mueller
authors: Jens
authors: J
authors: Guehring
mesh_terms: D000465:Algorithms; D001331:Automation; D003952:Diagnostic Imaging / Q000379:methods*; D006321:Heart / Q000033:anatomy & histology*; D006352:Heart Ventricles; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D015233:Models, Statistical; D009206:Myocardium / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*