Title :
AutoMPR: Automatic detection of standard planes in 3D echocardiography
Author :
Lu, Xiaoguang ; Georgescu, Bogdan ; Zheng, Yefeng ; Otsuki, Joanne ; Comaniciu, Dorin
Author_Institution :
Siemens Corp. Res., Princeton, NJ
Abstract :
3D echocardiography is one of the emerging real-time imaging modalities that is increasingly used in clinical practice to assess cardiac functions. It provides a more complete heart representation for evaluation in comparison to conventional 2D echocardiography. However, one of the drawbacks is the time it takes clinicians to navigate the 3D volumes to the anatomy of interest and to obtain standardized views that are similar to the 2D acquisitions. We propose an automated supervised learning method to detect standard multiplanar reformatted planes (MPRs) from a 3D echocardiographic volume. Extensive evaluations on a database of 326 volumes show performance comparable to intra-user variability and the execution time of the algorithm is about 2 seconds.
Keywords :
echocardiography; learning (artificial intelligence); medical computing; 3D echocardiography; AUTOMPR; automated supervised learning; automatic standard plane detection; cardiac function; heart representation; intra-user variability; real-time imaging modality; standard multiplanar reformatted planes; Anatomy; Biomedical imaging; Echocardiography; Heart; Image analysis; Image quality; Image reconstruction; Information analysis; Navigation; Robustness; Three-dimensional echocardiography; multiplanar reformatted/reconstruction (MPR); standard views;
Conference_Titel :
Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-2002-5
Electronic_ISBN :
978-1-4244-2003-2
DOI :
10.1109/ISBI.2008.4541237