International Journal of Engineering Research in Electronics and Communication Engineering(IJERECE)

Monthly Journal for Electronics and Communication Engineering

Volume5,April 2018,

Topic : Development of an Image-Based Modelling Tool for the Spinal Deformity Detection Using Curve Fitting Technique

Authors:Tabitha Janumala || Dr.K.B.Ramesh, Harish A Haralachar

Abstract:Scoliosis is a 3-dimensional abnormality of the spine that usually found in 2- 4% of adolescents population stated by the statistics of the country for scoliosis. Scoliosis is a disorder in which there is a sideways curve of the spine. Curves are often S-shaped or C-shaped. One of the methods to ascertain a patient with scoliosis is through using Cobb angle measurement. Any Cobb angle measurement takes about 20 – 30 minutes of inter and intraobserver. Scoliosis prediction is of great significance to reduce the uncertainty for doctors on deciding the optimum treatment for patients. Therefore the importance of the automatic spinal curve detection system is to detect any spinal disorder quicker and faster. The challenging task in computerized method lies in totally automating the method of curvature measurement from digital X-ray images. The importance of the automatic spine curve detection system is to detect ant spinal disorder quicker and faster. The proposed research work uses a template matching based on Sum of Squared Difference (SSD) to estimate the location of vertebrae. By using polynomial curve fitting method, spinal curvature estimation can be done. In this paper, the performance of SSD used to detect a variety of data sources of X-ray from numerous patients.The results from the implementation indicate that the proposed algorithm can be used to detect all the X-ray images..

Keywords: Cobb angle, Sum of Squared Difference (SSD), polynomial curve fitting method.

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DOI: 01.1617/vol5/iss4/pid68305

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Dr.Zhongfu Tan
National Professor,
North China Electric Power University,

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ISSN(Online): 2394-6849

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJERECE
Electronic ISSN : 2394-6849
Impact Factor : 3.689
Frequency : monthly
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