Name
Abstract | ||
|---|---|---|
Flow Doppler imaging has become an integral part of an echocardiographic exam. Automated interpretation of flow doppler imaging has so far been restricted to obtain- ing hemodynamic information from velocity-time profiles depicted in these images. In this paper we exploit the shape patterns in Doppler images to infer the similarity in valvu- lar disease labels for purposes of automated clinical deci- sion support. Specifically, we model the similarity in ap- pearance of Doppler images from the same disease class as a constrained non-rigid translation transform of the veloc- ity envelopes embedded in these images. The shape simi- larity between two Doppler images is then judged by recov- ering the alignment transform using a variant of dynamic shape warping. Results of similarity retrieval of doppler images for cardiac decision support on a large database of images are presented. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CVPR.2010.5540126 | Computer Vision and Pattern Recognition |
Keywords | Field | DocType |
cardiology,decision support systems,diseases,electrocardiography,flow visualisation,haemodynamics,image retrieval,medical image processing,cardiac decision support,clinical decision support,constrained nonrigid translation transform,dynamic shape warping,echocardiographic exam,flow Doppler imaging,hemodynamic information,shape-based similarity retrieval,valvular disease labels,velocity-time profiles | Computer vision,Image warping,Doppler imaging,Pattern recognition,Computer science,Decision support system,Valvular disease,Image retrieval,Pixel,Artificial intelligence,Clinical decision support system,Doppler effect | Conference |
Volume | ISSN | ISBN |
2010 | 1063-6919 | 978-1-4244-6984-0 |
Citations | PageRank | References |
6 | 0.72 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Syeda-Mahmood, T. | 1 | 6 | 0.72 |
| Turaga, P. | 2 | 6 | 0.72 |
| Beymer David | 3 | 420 | 87.32 |
| Fei Wang | 4 | 145 | 11.38 |