TA : Segmentasi Kelengkungan Tulang Belakang pada Penderita Skoliosis Menggunakan GVF Snake
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Institusion
Universitas Dinamika
Author
Sugianto, Samuel
Susijanto Tri Rasmana (LECTURER ID : .)
Madha Christian Wibowo (LECTURER ID : .)
Susijanto Tri Rasmana (LECTURER ID : .)
Madha Christian Wibowo (LECTURER ID : .)
Subject
610 Medical sciences; Medicine
Datestamp
2015-07-29 02:38:12
Abstract :
Scoliosis is a spinal deformity phenomenon that will bend to form the letter C or S. Degree of spinal curvature determines the severity of scoliosis that occurs so that a proper diagnosis would provide a great chance of recovery for patients. Current diagnosis of curvature of spine orthopedic done manually by giving a potential for measurement error cobb angle (degree of curvature). Image Processing rapid development currently provides a solution to overcome the above problems. In this study, made application to the segmentation of the spine that uses Gaussian cropping and Modified Tophat filter for pre-processing and segmentation GVF Snake for curvature of the spine. This application can perform segmentation of spinal curvature on some form of spine and help reduce the rate of misdiagnosis in patients with scoliosis caused by manual measurements with an average accuracy rate of 79.355%.
Scoliosis is a spinal deformity phenomenon that will bend to form the letter C or S. Degree of spinal curvature determines the severity of scoliosis that occurs so that a proper diagnosis would provide a great chance of recovery for patients. Current diagnosis of curvature of spine orthopedic done manually by giving a potential for measurement error cobb angle (degree of curvature). Image Processing rapid development currently provides a solution to overcome the above problems. In this study, made application to the segmentation of the spine that uses Gaussian cropping and Modified Tophat filter for pre-processing and segmentation GVF Snake for curvature of the spine. This application can perform segmentation of spinal curvature on some form of spine and help reduce the rate of misdiagnosis in patients with scoliosis caused by manual measurements with an average accuracy rate of 79.355%.
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