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Aims: To improve visualisation of angiographic features in patients with age r elated macular degeneration associated with choroidal neovascularisation (CNV) a nd related complications. To evaluate if image averaging can achieve this goal. Methods: 27 eyes of 20 sequential patients with age related macular degeneration over a 3 month period were studied. Indocyanine green angiograms (ICGA), fluore scein angiograms (FA), and oral fluorescein angiograms were recorded with a conf ocal scanning laser ophthalmoscope. Software was used to average multiple images from a 10-20 image series (over 0.5-1.0 seconds). Image quality was assessed by two masked observers and graded on a scale of 0-3. A more quantifiable gradi ng method was devised by adding a variable amount of Gaussian noise to the impro ved image until the original and image averaged image appeared equal. Results: M asked review showed mild to strong improvement of visualisation of structures in cluding borders of CNV. Improvement varied depending on the type and phase of th e angiogram. Improvement was highest in late phase FA, mid and late phase ICGA, and all phases of oral FA. Conclusion: Image averaging using software based algo rithms improves the quality of angiographic images, particularly late ICGA image s and oral FAs. This method may assist in the visualisation of choroidal neovasc ularisation in age related macular degeneration.
Aims: To improve visualization of angiographic features in patients with age-related macular degeneration associated with choroidal neovascularisation (CNV) a nd related complications. To evaluate if image averaging can achieve this goal. Methods: 27 eyes of 20 sequential patients with age related macular degeneration over a 3 month period were studied. Indocyanine green angiograms (ICGA), fluore scein angiograms (FA), and oral fluorescein angiograms were recorded with a conf ocal scanning laser ophthalmoscope. Software was used to average multiple images from a 10-20 image series (over 0.5-1.0 seconds). Image quality was assessed by two masked observers and graded on a scale of 0-3. A more quantifiable gradi ng method was devised by adding a variable amount of Gaussian noise to the impro ved image until the original and image averaged image Even equal. Results: M asked review showed mild to strong improvement of visualization of structures in cluding borders of CNV. Improvement v arment depending on the type and phase of th e angiogram. Improvement was highest in late phase FA, mid and late phase ICGA, and all phases of oral FA. Conclusion: Image averaging using software based algo rithms improves the quality of angiographic images late ICGA image s and oral FAs. This method may assist in the visualization of choroidal neovasc ularisation in age related macular degeneration.