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    <titleInfo>
        <title>A hybrid segmentation approach for geographic atrophy in fundus auto-fluorescence images for diagnosis of age-related macular degeneration</title>
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    <name type="personal" ID="nl2168">
        <namePart type="family">Lee</namePart>
        <namePart type="given">Noah</namePart>
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        <affiliation>Columbia University. Biomedical Engineering</affiliation>
        <affiliation>Columbia University. Ophthalmology</affiliation>
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    <name type="personal" ID="al418">
        <namePart type="family">Laine</namePart>
        <namePart type="given">Andrew F.</namePart>
        <role>
            <roleTerm type="text">author</roleTerm>
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        <affiliation>Columbia University. Biomedical Engineering</affiliation>
        <affiliation>Columbia University. Radiology</affiliation>
    </name>
    <name type="personal" ID="rts1">
        <namePart type="family">Smith</namePart>
        <namePart type="given">R. Theodore</namePart>
        <role>
            <roleTerm type="text">author</roleTerm>
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        <affiliation>Columbia University. Ophthalmology</affiliation>
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        <namePart>Columbia University. Biomedical Engineering</namePart>
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    <abstract>Fundus auto-fluorescence (FAF) images with hypo-fluorescence indicate geographic atrophy (GA) of the retinal pigment epithelium (RPE) in age-related macular degeneration (AMD). Manual quantification of GA is time consuming and prone to inter- and intra-observer variability. Automatic quantification is important for determining disease progression and facilitating clinical diagnosis of AMD. In this paper we describe a hybrid segmentation method for GA quantification by identifying hypo-fluorescent GA regions from other interfering retinal vessel structures. First, we employ background illumination correction exploiting a non-linear adaptive smoothing operator. Then, we use the level set framework to perform segmentation of hypo-fluorescent areas. Finally, we present an energy function combining morphological scale-space analysis with a geometric model-based approach to perform segmentation refinement of false positive hypo- fluorescent areas due to interfering retinal structures. The clinically apparent areas of hypo-fluorescence were drawn by an expert grader and compared on a pixel by pixel basis to our segmentation results. The mean sensitivity and specificity of the ROC analysis were 0.89 and 0.98%.</abstract>
    <note type="reference">2007 Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Lyon, France, 22-26 August 2007 (Piscataway, N.J.: IEEE, 2007), pp. 4965-4968.</note>
    <subject>
        <topic>Biomedical engineering</topic>
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    <identifier type="doi">http://dx.doi.org/10.1109/IEMBS.2007.4353455</identifier>
    <identifier type="hdl">http://hdl.handle.net/10022/AC:P:9455</identifier>
    
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