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Registration and fusion of the autofluorescent and infrared retinal images.

Kolar R, Kubecka L, Jan J - Int J Biomed Imaging (2008)

Bottom Line: This article deals with registration and fusion of multimodal opththalmologic images obtained by means of a laser scanning device (Heidelberg retina angiograph).The registration framework has been designed and tested for combination of autofluorescent and infrared images.Two fusion methods are presented and compared.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Kolejni 4, 61200 Brno, Czech Republic. kolarr@feec.vutbr.cz

ABSTRACT
This article deals with registration and fusion of multimodal opththalmologic images obtained by means of a laser scanning device (Heidelberg retina angiograph). The registration framework has been designed and tested for combination of autofluorescent and infrared images. This process is a necessary step for consecutive pixel level fusion and analysis utilizing information from both modalities. Two fusion methods are presented and compared.

No MeSH data available.


The metric plane shown as 2D images for IR and AF images. The brigthnessrepresents similarity value: (a) MSS, (b) NCC, (c) MI. The proper shift values arelocated at (0,0) position.
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Related In: Results  -  Collection


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fig5: The metric plane shown as 2D images for IR and AF images. The brigthnessrepresents similarity value: (a) MSS, (b) NCC, (c) MI. The proper shift values arelocated at (0,0) position.

Mentions: The above-mentioned metrics were evaluated for thedefined shifts pixel by pixel, using several pairs of AF and IR images. Theexamples of these metric surfaces are depicted on Figure 5. One can see that theNCC and MSD similarity metrics have quite similar surfaces. More detailedexamination showed that the NCC metric plane has sharper global maximum formajority of the tested images. It also has less local extremes, which iswelcome in optimization. Comparing NCC and MI metric planes, the MI metricshows also good properties for optimization. But, considering the computationalcomplexity, we decided to use the NCC metric, according to the definition[27] (5)NCC(F, G) = ∑i=1NFi⋅Gi∑i=1NFi2⋅∑i=1NGi2, where Fi and Gi represent the pixel values of gradient imagesand N is number of pixels in the overlapping region.The means were subtracted before NCC computation.


Registration and fusion of the autofluorescent and infrared retinal images.

Kolar R, Kubecka L, Jan J - Int J Biomed Imaging (2008)

The metric plane shown as 2D images for IR and AF images. The brigthnessrepresents similarity value: (a) MSS, (b) NCC, (c) MI. The proper shift values arelocated at (0,0) position.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2570800&req=5

fig5: The metric plane shown as 2D images for IR and AF images. The brigthnessrepresents similarity value: (a) MSS, (b) NCC, (c) MI. The proper shift values arelocated at (0,0) position.
Mentions: The above-mentioned metrics were evaluated for thedefined shifts pixel by pixel, using several pairs of AF and IR images. Theexamples of these metric surfaces are depicted on Figure 5. One can see that theNCC and MSD similarity metrics have quite similar surfaces. More detailedexamination showed that the NCC metric plane has sharper global maximum formajority of the tested images. It also has less local extremes, which iswelcome in optimization. Comparing NCC and MI metric planes, the MI metricshows also good properties for optimization. But, considering the computationalcomplexity, we decided to use the NCC metric, according to the definition[27] (5)NCC(F, G) = ∑i=1NFi⋅Gi∑i=1NFi2⋅∑i=1NGi2, where Fi and Gi represent the pixel values of gradient imagesand N is number of pixels in the overlapping region.The means were subtracted before NCC computation.

Bottom Line: This article deals with registration and fusion of multimodal opththalmologic images obtained by means of a laser scanning device (Heidelberg retina angiograph).The registration framework has been designed and tested for combination of autofluorescent and infrared images.Two fusion methods are presented and compared.

View Article: PubMed Central - PubMed

Affiliation: Department of Biomedical Engineering, Faculty of Electrical Engineering and Communication, Brno University of Technology, Kolejni 4, 61200 Brno, Czech Republic. kolarr@feec.vutbr.cz

ABSTRACT
This article deals with registration and fusion of multimodal opththalmologic images obtained by means of a laser scanning device (Heidelberg retina angiograph). The registration framework has been designed and tested for combination of autofluorescent and infrared images. This process is a necessary step for consecutive pixel level fusion and analysis utilizing information from both modalities. Two fusion methods are presented and compared.

No MeSH data available.