Automated change analysis from fluorescein angiograms for monitoring wet macular degeneration

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn , Issue , 2006, Pages 4714-4717

  Narasimha Iyer, Harihar ^a   Can, Ali ^a   Roysam, Badrinath ^a   Stern, Jeffrey ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; IMAGE ANALYSIS; MEDICAL COMPUTING; PATIENT MONITORING; TIME SERIES ANALYSIS; VISION;

FLUORESCEIN ANGIOGRAMS (FA); RETINAL IMAGES; WET MACULAR DEGENERATION;

ANGIOGRAPHY;

FLUORESCEIN;

ALGORITHM; ANGIOGRAPHY; ARTICLE; AUTOMATED PATTERN RECOGNITION; AUTOMATION; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; EQUIPMENT; EQUIPMENT DESIGN; FLUORESCENCE ANGIOGRAPHY; HUMAN; METHODOLOGY; OPTIC DISK; PATHOLOGY; REPRODUCIBILITY; RETINA MACULA DEGENERATION; SUBRETINAL NEOVASCULARIZATION;

ALGORITHMS; ANGIOGRAPHY; AUTOMATION; BAYES THEOREM; CHOROIDAL NEOVASCULARIZATION; EQUIPMENT DESIGN; FLUORESCEIN; FLUORESCEIN ANGIOGRAPHY; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MACULAR DEGENERATION; OPTIC DISK; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SOFTWARE;

EID: 34047137928     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2006.259738     Document Type: Conference Paper

References (13)

1. F.L. Ferris 3rd, S.L Fine and L. Hyman, "Age-related macular degeneration and blindness due to neovascular maculopathy", Archives of Opthalmology, vol. 102, no. 11, 1984, pp 1640-1642.
2. H. Narasimha-Iyer, A.Can, B.Roysam, C.V. Stewart, H. L. Tanenbaum, A. Majerovics and H. Singh, Automated Analysis of Longitudinal Changes in Color Retinal Fundus Images for Monitoring Diabetic Retinopathy, IEEE Transactions on Biomedical Engineering, May 2005.
3. A. Can, H. Shen, J. N. Turner, H. L. Tanenbaum and B. Roysam, "Rapid Automated Tracing and Feature Extraction From Live High-resolution Retinal Fundus Images Using Direct Exploratory Algorithms", IEEE Transactions on Information Technology in BioMedicine, vol. 3, no.2, June 1999, pp 125-138.
4. K. H. Fritzsche, A. Can, H. Shen, C. Tsai, J. N. Turner, H. L. Tanenbaum, C.V. Stewart and B. Roysam, "Angiography and Plaque Imaging: Advanced Segmentation Methods. Chapter:Automated Model Based Segmentation, Tracing, and Analysis of Retinal Vasculature from Digital Fundus Images",CRC Press, Boca Raton.
5. A. Hoover and M. Goldbaum, "Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessel", IEEE Transactions on Meedical Imaging, vol. 22, no. 8, 2003, pp 951-958.
6. A. Pinz, S. Bernogger, P. Datlinger and A. Kruger, "Mapping the human retina", IEEE Transactions on Medical Imaging, vol. 17, 1998, pp 606-619.
7. C.V. Stewart, C.L. Tsai and B. Roysam, "The Dual-Bootstrap Iterative Closest Point algorithm with application to retinal image registration", IEEE Transactions on Medical Imaging, vol. 22, no. 11, 2003, pp 1379-1394.
8. A. Can, C.V. Stewart, B. Roysam, and H.L. Tanenbaum, "A feature-based, robust, hierarchical algorithm for registering pairs of images of the curved human retina", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no.3, 2002, pp 347-363.
9. R. Adams and L. Bischof, "Seeded region growing", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 16, no.6, 1994, pp 641-647.
10. S.-Y. Wan and W.E. Higgins, "Symmetric Region Growing", IEEE Transactions on Image Processing, vol. 12, no.9, 2003, pp 1007-1015.
11. A. Dempster, N. Laird and D. Rubin,"Maximum likelihood from incomplete data via the EM algorithm", Journal of the Royal Statistical Society, vol. 39, 1977, pp 1-38.
12. P. Paalanen, J.-K Kamarainen, J. Ilonen and H. Klviinen, "Feature Representation and Discrimination Based on Gaussian Mixture Model Probability Densities - Practices and Algorithms", Technical Report, Lappeenranta University of Technology, Department of Information Technology, 2005.
13. T. Aach and A. Kaup,"Bayesian algorithms for adaptive change detection in image sequences using Markov Random Fields", Signal Processing: Image Communication, vol. 7, 1997, pp 147-160.