Dust Particle Artifact Detection and Removal in Retinal Images
E. Sierra, A. G. Marrugo, M. S. Millán
Download Paper
Base Information
Volume
V50 - N4 / 2017 Ordinario
Reference
379-387
DOI
http://doi.org/10.7149/OPA.50.4.49075
Language
English
Keywords
Dust particle artifacts, retinal image, inpainting, artifact localization, retinal image enhancement.
Abstract
Retinal fundus cameras suffer from dust particles attaching to the sensor and lens, which manifest as small artifacts on the images. We propose a new strategy for the detection and removal of dust particle artifacts in retinal images. We consider as input two or more color fundus images acquired within the same session, in which we assume the artifacts remain in the same position. Our method consists in detecting candidate artifacts via normalized cross correlation with an artifact template, performing segmentation via region growing, and comparing the segmentations in all images. This guarantees that all detections are consistent for all images. The removal stage consists in an inpainting procedure so that the new region does not stand out from the neighboring regions. Encouraging experimental results show the localization of artifacts is effective and the artifacts are successfully removed, while not introducing new artifacts in the color retinal images.
References
M. D. Abramoff, M. Garvin, and M. Sonka, "Retinal Imaging and Image Analysis," Biomedical Engineering, IEEE Reviews in, 3, 169–208 (2010).
R. G. Willson, M. Maimone, A. Johnson, and L. Scherr, An optical model for image artifacts produced by dust particles on lenses. 2005, 1–8.
C. Zhou and S. Lin, "Removal of Image Artifacts Due to Sensor Dust," 1–8, Apr. 2007.
A. D. Mora, J. Soares, and J. M. Fonseca, "A template matching technique for artifacts detection in retinal images," presented at the 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA), 717–722.
M. Niemeijer, M. D. Abramoff, and B. van Ginneken, "Image structure clustering for image quality verification of color retina images in diabetic retinopathy screening," Medical Image Analysis, 10, 888–898 (2006).
A. G. Marrugo, M. S. Millan, G. Cristóbal, S. Gabarda, and H. C. Abril, "No-reference Quality Metrics for Eye Fundus Imaging," CAIP 2011, LNCS, 6854, 486–493 (2011).
T. Köhler, A. Budai, M. Kraus, J. Odstrcilik, G. Michelson, and J. Hornegger, "Automatic no-reference quality assessment for retinal fundus images using vessel segmentation.," presented at the IEEE 26th International Symposium on Computer-Based Medical Systems (CBMS), 2013, 95–100.
S. A. Ali Shah, A. Laude, I. Faye, and T. B. Tang, "Automated microaneurysm detection in diabetic retinopathy using curvelet transform," J. Biomed. Opt., 21, 101404 (2016).
P. Yang, L. Chen, J. Tian, and X. Xu, "Dust particle detection in surveillance video using salient visual descriptors," Computers & Electrical Engineering, 2016.
L. Chen, D. Zhu, J. Tian, and J. Liu, "Dust particle detection in traffic surveillance video using motion singularity analysis," Digit Signal Process, 1–7 (2016).
A. G. Marrugo, E. Sierra, and M. S. Millan, "Dust Particle Detection and Correction in Retinal Images," presented at the RIAO-OPTILAS 2016, Pucón, Chile, 268, 2016.
R. Radke, S. Andra, O. Al-Kofahi, and B. Roysam, "Image change detection algorithms: a systematic survey," Image Processing, IEEE Transactions on, 14, 294–307 (2005).
A. G. Marrugo, M. Sorel, F. Sroubek, and M. S. Millan, "Retinal image restoration by means of blind deconvolution," J. Biomed. Opt., 16, 116016 (2011).
A. G. Marrugo and M. S. Millan, "Retinal Image Analysis Oriented to the Clinical Task," Electronic Letters on Computer Vision and Image Analysis, 13, 54–55 (2014).
R. C. Gonzalez, R. E. Woods, and S. L. Eddins, Digital Image Processing Using MATLAB®. McGraw Hill Education, 2010.
D.-M. Tsai and C.-T. Lin, "Fast normalized cross correlation for defect detection," Pattern Recognition Letters, 24, 2625–2631 (2003).
A. G. Marrugo and M. S. Millan, "Optic disc segmentation in retinal images," Opt. Pura Apl., 43, 79–86(2010).
A. Neubeck and L. Van Gool, "Efficient non-maximum suppression," presented at the Pattern Recognition, 2006. ICPR 2006. 18th International Conference on, 2006, 3, 850–855.
R. M. Haralick, S. R. Sternberg, and X. Zhuang, "Image analysis using mathematical morphology," Pattern Analysis and Machine Intelligence, IEEE Transactions on Pattern Analysis and Machine Intelligence, 9, 532–550 (1987).