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Analysis of Fluorescein Angiogram for Monitoring Treatment Effectiveness of Retinal Vascular Disorder Wen-Chyi Lin University of Pittsburgh, Pittsburgh,

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Presentation on theme: "Analysis of Fluorescein Angiogram for Monitoring Treatment Effectiveness of Retinal Vascular Disorder Wen-Chyi Lin University of Pittsburgh, Pittsburgh,"— Presentation transcript:

1 Analysis of Fluorescein Angiogram for Monitoring Treatment Effectiveness of Retinal Vascular Disorder Wen-Chyi Lin University of Pittsburgh, Pittsburgh, PA 15261 2016.03

2 Introduction Retinal vascular disease has become the most common cause of visual impairment and blindness in industrialized countries Age-related Macular Degeneration (AMD) Diabetic Macular Oedema (DMO) Retinal Vein Occlusion (RVO) Fluorescein angiography provides superb visualization of vascular abnormalities Morphological lesions vary in shape, size, location, dynamics can be diagnosed via retina evaluation

3 Motivation Normal vasculatures are line segments while irregular lesions usually associated with exudates, cotton-wool spots and drusen patterns Curvelets have significant advantages of capturing singularities in images with multiresolution geometric properties Monitoring of these signs in retina images can help to identify the presence of a specific disease entity and appropriate treatment prevents ophthalmologic complications and vision loss

4 Curvelet Transform Curvelet transform was developed by E. J. Candes and D. L. Donoho for an optimal sparse representation of functions with curvilinear singularities. The fast discrete curvelet transform was published in Multiscale Modeling & Simulations, 2006, and the software is available in Curvelab Toolbox at CIT. For applications to image processing, it provides a very efficient approach for representing images containing curvilinear structures, and thus for image denoising, image fusion, texture classification, and inverse problems

5 Property of Curvelets

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8 Retinal Singularity Map

9 Fine Scale Coarse Scale Multiresolution Analysis Curvelets apprehend different structures of retinal vascular in a multi-scale sense Abnormalities can be monitored and comparison of prognosis between treatments can be performed easily Multiresolution

10 Multiresolution Coarse Scale Fine Scale 1 2 3 4 FA Image Before Treatment

11 1 2 3 4 FA Image After Treatments

12 2015.07.22 Before Treatment2016.01.22 After Treatments The curvelets clearly capture the singularities of retinal vascular branches in fluorescein angiography images Left: growth of abnormality before treatment Right: decrease of lesions after several Eylea injections 1 1

13 2015.07.22 Before Treatment2016.01.22 After Treatments The growth of abnormalities after treatments are shown in the red circles 22

14 2015.07.22 Before Treatment2016.01.22 After Treatments Not visible abnormality in 2015 was enhanced and was controlled in 2016 3 3

15 2015.07.22 Before Treatment 2016.01.22 After Treatments 4 4 Growth of abnormality in 2015 was controlled in 2016


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