Visual saliency based bright lesion detection and discrimination in retinal images

Proceedings - International Symposium on Biomedical Imaging

Volumn , Issue , 2013, Pages 1436-1439

  Ujjwal, ^a   Deepak, K Sai ^a   Chakravarty, Arunava ^a   Sivaswamy, Jayanthi ^a  

^a INTERNATIONAL INSTITUTE OF INFORMATION TECHNOLOGY   (India)

Author keywords

Abnormality Detection; Bright Lesion Detection; Color Fundus Images; Visual Saliency

Indexed keywords

ABNORMALITY DETECTION; AREA UNDER ROC CURVE (AUC); AUTOMATED IMAGE ANALYSIS; FUNDUS IMAGE; IMAGE-BASED DIAGNOSIS; LESION DETECTION; SPARSE REPRESENTATION; VISUAL SALIENCY;

COMPUTER AIDED DIAGNOSIS; MEDICAL IMAGING; OPHTHALMOLOGY;

VISUALIZATION;

EID: 84881631759     PISSN: 19457928     EISSN: 19458452     Source Type: Conference Proceeding    
DOI: 10.1109/ISBI.2013.6556804     Document Type: Conference Paper

References (16)

1. Nodine et.al, "Using eye movements to study visual search and to improve tumor detection," Radiographics, vol. 7, no. 6, pp. 1241-1250, 1987.
2. Matsumoto et.al, "Where do neurologists look when viewing brain ct images? an eye-tracking study involving stroke cases," PloS one, vol. 6, no. 12, pp. e28928, 2011.
3. Harel et.al, "Graph-based visual saliency," in NIPS, 2006, pp. 545-552.
4. Jampani et.al, "Assessment of computational visual attention models on medical images," in Indian conf. on vis. graphics and img. proc. ICVGIP, 2012.
5. Niemeijer et.al., "Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis," Invest Ophthalmol Vis Sci., vol. 48, no. 5, pp. 2260-2267, 2007. (Pubitemid 351261304)
6. Rocha et.al, "Points of interest and visual dictionaries for automatic retinal lesion detection," Biomed. Engg., IEEE Trans. on, vol. 59, no. 8, pp. 2244 -2253, aug. 2012.
7. KS. Deepak and J. Sivaswamy, "Automatic assessment of macular edema from color retinal images," IEEE Trans. Med. Img., vol. 31, no. 3, pp. 766-776, 2012.
8. Giancardo et.al., "Automatic retina exudates segmentation without a manually labelled training set," in ISBI, 30 2011-april 2 2011, pp. 1396-1400.
9. Agurto et.al, "Multiscale am-fm methods for diabetic retinopathy lesion detection.," IEEE Trans. Med. Imaging, vol. 29, no. 2, pp. 502-512, 2010.
10. Freund et.al, "Automated detection of drusen in the macula," 2009, ISBI'09, pp. 61-64.
11. Quellec et.al, "Optimal filter framework for automated, instantaneous detection of lesions in retinal images.," IEEE Trans. Med. Imaging, vol. 30, pp. 523-533, 2011.
12. X. Hou and L. Zhang, "Saliency detection: A spectral residual approach," in CVPR07, 2007, pp. 1-8.
13. Deepak et.al, "Detection and discrimination of disease-related abnormalities based on learning normal cases," PR, vol. 45, no. 10, pp. 3707-3716, 2012.
14. Welfer et.al., "A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images," Comp. Med. Img. Graphics CMIG, vol. 34, no. 3, pp. 228 - 235, 2010.
15. Hijazi et.al, "Retinal image classification for the screening of agerelated macular degeneration," in The 30th SGAI Int. Conf. on Innovative Tech. and App. of AI, 2010, pp. 325-338.
16. L. Brandon and A. Hoover, "Drusen detection in a retinal image using multi-level analysis," in MICCAI, 2003, pp. 618-625.