24 research outputs found

    Analysis of the Gene and Protein Causing Best Macular Dystrophy

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    Best macular dystrophy (BMD) is an autosomal dominant inherited eye disease with a juvenile onset. Accumulation of the pigment lipofuscin in the retinal pigment epithelium can later cause macular degeneration and loss of vision. BMD have histopathologic similarities with age-related macular degeneration, the most common cause of blindness among elderly. BMD diagnosis is made with fundus examination and electrophysiology. The VMD2 gene, causing BMD, has previously been localized to 11q13 using linkage and recombination of a 12 generation family with BMD. In this study the genetic region has been further narrowed using polymorphic markers in the BMD family. A human homolog for a C. elegans protein family, expressed in retina, was identified as the VMD2 gene. It has a 1755 bp open reading frame with 11 exons and encodes a 585 amino acid protein called bestrophin. Mutation analysis of the VMD2 gene in BMD families from Sweden, Denmark and Netherlands revealed 15 missense mutations, altering single amino acids in bestrophin, accumulating in the N-terminal half of the protein. VMD2 expression analysis with in situ hybridization revealed specific localization in the retinal pigment epithelium and Northern blot showed expression in retina and brain. Clinical and genetic analysis of a BMD family with generally late onset revealed a novel bestrophin mutation. Analysis of mouse Vmd2 and bestrophin during development showed presence of mouse bestrophin in retinal pigment epithelium at postnatal day 10 and in photoreceptor outer segments during the entire postnatal period. Vmd2 expression levels were highest around birth

    Retinal Vessel Width Measurement at Branchings Using an Improved Electric Field Theory-Based Graph Approach

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    The retinal vessel width relationship at vessel branch points in fundus images is an important biomarker of retinal and systemic disease. We propose a fully automatic method to measure the vessel widths at branch points in fundus images. The method is a graph-based method, in which a graph construction method based on electric field theory is applied which specifically deals with complex branching patterns. The vessel centerline image is used as the initial segmentation of the graph. Branching points are detected on the vessel centerline image using a set of detection kernels. Crossing points are distinguished from branch points and excluded. The electric field based graph method is applied to construct the graph. This method is inspired by the non-intersecting force lines in an electric field. At last, the method is further improved to give a consistent vessel width measurement for the whole vessel tree. The algorithm was validated on 100 artery branchings and 100 vein branchings selected from 50 fundus images by comparing with vessel width measurements from two human experts

    An illustration of the human expert annotation.

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    <p>Blue dots denote the region where the measurement should be given. Black text were superimposed by the author for the sake of illustration. Vessel width for branch 1 is calculated as the average of the three width profiles. The branch center for branch 1 is calculated as the average of the three width profile center.</p
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