Cardiac view classification using speed up robust features

Indian Journal of Science and Technology

Volumn 8, Issue , 2015, Pages 1-5

  Balaji, G N ^a   Subashini, T S ^a   Chidambaram, N ^a  

^a ANNAMALAI UNIVERSITY   (India)

Author keywords

Apical four chamber (A4C); Apical two chamber (A2C); Echocardiogram; Parasternal long axis (PLAX); Parasternal short axis (PsAX); Speed up robust features (SURF)

Indexed keywords

EID: 84928784420     PISSN: 09746846     EISSN: 09745645     Source Type: Journal    
DOI: 10.17485/ijst/2015/v8iS7/62245     Document Type: Article

References (18)

1. Turk MA, Pentland AP. Face recognition using eigen faces. IEEE Computer Society Conference on Computer Vision and Pattern Recognition; 1991 Jun. p. 586-91.
2. SURF Source code. Availaible from: http://www.vision. ee.ethz.ch/~surf/.
3. Bay H, Tuytellars T, Gool L. SURF: Speeded up robust features. European Conferecne on Computer Vision; 2006.
4. Lowe D. Distincitive image features from scale-invariant keypoints. Int J Comput Vis. 2004.
5. Turk MA. Pentland AP. Face recognition using eigenfaces. IEEE Computer Society Conference on Computer Vision and Pattern Recognition; 1991 Jun. p. 586-91.
6. Ebadollahi S, Chang S-F, Wu H. Automatic view recognition in echocardiogram videos using parts-based representation. Proceedings of the 2004 IEEE Computer Society Conference on Com-puter Vision and Pattern Recognition, 2004. CVPR 2004; IEEE; 2004. p. II-2-II-9.
7. Zhou XS, Comaniciu D, Gupta A. An information fusion framework for robust shape tracking. PAMI. 2005 Jan; 27(1):115-29.
8. Park, JH. Automatic cardiac view classification of echocardiogram. IEEE 11th International Con-ference on Computer Vision, 2007. ICCV 2007; IEEE; 2007.
9. Roy A. State-based modeling and object extraction from echocardiogram video. IEEE Trans In-form Tech Biomed. 2008; 12(3):366-76.
10. Zhou SK, Park JH, Georgescu B, Simopoulos C, Otsuki J, Comaniciu D. Image based multiclass boosting and echocardiographic view classification. IEEE Conference on Computer Vision and Pattern Recognition; 2006.
11. Hasanuzzaman FM, Yang X. Tian YL. Robust and effective component-based banknote recognition by SURF features. 20th Annual Wireless and Optical Communications Conference (WOCC); IEEE; 2011.
12. Khan, NY, McCane B, Wyvill G. Sift and surf performance evaluation against various image de-formations on benchmark dataset. 2011 International Conference on Digital Image Computing Techniques and Applications (DICTA); IEEE; 2011.
13. Bay H, Tuytelaars T, Van Gool L. SURF: Speeded up robust features. Proceedings European Con-ference on Computer Vision. 2006; 110:407-17.
14. Evans C. Notes on the OpenSURF library. University of Bristol (UK); 2009. Available from http://www. chrisevansdev.com.
15. Lin, SD, Liu B, Lin J. Combining speeded-up robust features with principal component analysis in face recognition system. International Journal of Innovative Computing, Information and Control. 2012; 8(12):8545-56.
16. Majumdar A, Ward RK. Discriminative SIFT features for face recognition. Canadian Conference on Electrical and Computer Engineering; 2009. p. 27-30.
17. Kavya G, Thulasibai V. VLSI Implementation of telemonitoring system for high risk cardiac patients. Indian Journal of Science and Technology. 2014 May; 7(5):571-6.
18. Balaji GN, Subashini TS, Suresh A. An efficient view classification of echocardiogram using morphological operations. J Theor Appl Inform Tech. 2014; 67(3).