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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fadzil, M.H.A. Nugroho, H.A. Nugroho, H. Iznita, I.L. |
| Copyright Year | 2009 |
| Abstract | Analyzing retinal fundus image is important for early detection of diseases related to the eye. However, in fundus images the contrast between retinal blood vessels and the background is very low. Hence, analyzing or visualizing tiny blood vessels is difficult. Fluorescein angiogram overcomes this imaging problem but it is an invasive procedure that leads to other physiological problems. In this work, we enhance the low contrast of retinal vasculature in the ocular fundus image by determining the retinal pigments makeup, namely haemoglobin, melanin and macular pigment using independent component analysis. Independent component image due to haemoglobin pigment obtained exhibits higher contrast retinal vasculature. Even though the fundus fluorescein angiograph method produces higher contrast images, results show that this approach outperforms other noninvasive enhancement method, such as contrast limited adaptive histogram equalization and can be beneficial for vessel segmentation. Contrast enhancement factor of 3.2 for digital retinal images is achieved. This improvement in contrast reduces the need of applying contrasting agent on patients. |
| Starting Page | 137 |
| Ending Page | 141 |
| File Size | 1098057 |
| Page Count | 5 |
| File Format | |
| ISBN | 9780769535654 |
| DOI | 10.1109/ICDIP.2009.32 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-03-07 |
| Publisher Place | Thailand |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Visualization Independent component analysis Blood vessels Adaptive equalizers Retina Diseases Histograms Image analysis independent component analysis Pigments fundus images retinal vasculature contrast enhancement Biomedical imaging |
| Content Type | Text |
| Resource Type | Article |
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