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Quantification of Retinal Vascular Tortuosity: Evaluation on Different Numbers of Sampling Points
Nafia T.D.a, Handayani A.a
a School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.Local tortuosity in a certain segment of the retinal blood vessels can be used to evaluate progression of some chronic diseases, such as diabetic and hypertensive retinopathy. To ensure objective and accurate observation on the progression of local vessel tortuosity, a quantitative tortuosity measurement index based on digital image processing is required. The generic first step in local tortuosity quantification is to isolate the local retinal blood vessel segment and represent it as series of sampling point coordinates through curve resampling and smoothing procedures. This paper presents the effects of different number of sampling points on the performance of the twelve different retinal local vascular tortuosity indexes. We seek to find the tortuosity index formulation which consistently shows strong correlation with the ophthalmologist assessment and the optimum number of sampling points required to achieve such performance. Our research confirmed that the Tortuosity Density (TD) index provides the highest spearman’s rank correlation coefficients with ophthalmolgist assessment, i.e. 0.94 for retinal arteries and 0.85 for retinal veins. This performance was achieved by three-times upsampling from the original vessel sampling points.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Chronic disease,Optimum number,Retinal blood vessels,Sampling points,Spearman’s rank correlation coefficients,Strong correlation,tortuosity,Up sampling[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]retinal blood vessel,sampling point,tortuosity[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/IBIOMED.2018.8534883[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]