Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip

Scoliosis is a medical condition that causes the spine to bend sideways either to the left or right. Some of the scoliosis type have the same appearance as the normal spine which can confused surgeons, physiatrists and academician when seeing them. It took a lot of time and energy to manually detect...

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Main Author: Mohd Hanip, Aisyah Afifah
Format: Thesis
Language:en
Published: 2020
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/31489/1/31489.pdf
https://ir.uitm.edu.my/id/eprint/31489/
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author Mohd Hanip, Aisyah Afifah
author_facet Mohd Hanip, Aisyah Afifah
author_sort Mohd Hanip, Aisyah Afifah
building Tun Abdul Razak Library
collection Institutional Repository
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
continent Asia
country Malaysia
description Scoliosis is a medical condition that causes the spine to bend sideways either to the left or right. Some of the scoliosis type have the same appearance as the normal spine which can confused surgeons, physiatrists and academician when seeing them. It took a lot of time and energy to manually detect Adolescent Idiopathic Scoliosis. The need for an application that can speed up the process and use a method that surgeons, physiatrists and academician would understand is certainly going to solve the problems. To overcome these problems, Identification of Adolescent Idiopathic Scoliosis application is built by using image processing. The technique used was by going through pre-processing, feature extraction and also classification as it is capable for the flow of the project. The pre-processing technique used are converting to grayscale image, implementing sharpening filter and median filter. As for feature extraction, gray level co-occurrence matrix is used. Ensemble classification, a model in which better predictive performance is achieved through the incorporation of the outputs of multiple classification models into a good classification process. The developed prototype is using 60 images. This system was tested for accuracy by calculating the percentage of the entire application accuracy. The result showed that the classification of ensemble would yield accurate result with the highest percentage of accuracy which is 86.67%. The research will help to identify more forms of Adolescent Idiopathic Scoliosis with a lot of data for the future work of the project. To help physicians and surgeons, computer-aided software will be built in the future for Adolescent Idiopathic Scoliosis.
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institution Universiti Teknologi Mara
language en
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spelling my.uitm.ir-314892020-06-26T04:16:51Z https://ir.uitm.edu.my/id/eprint/31489/ Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip Mohd Hanip, Aisyah Afifah Cartography Instruments and machines Electronic Computers. Computer Science Scoliosis is a medical condition that causes the spine to bend sideways either to the left or right. Some of the scoliosis type have the same appearance as the normal spine which can confused surgeons, physiatrists and academician when seeing them. It took a lot of time and energy to manually detect Adolescent Idiopathic Scoliosis. The need for an application that can speed up the process and use a method that surgeons, physiatrists and academician would understand is certainly going to solve the problems. To overcome these problems, Identification of Adolescent Idiopathic Scoliosis application is built by using image processing. The technique used was by going through pre-processing, feature extraction and also classification as it is capable for the flow of the project. The pre-processing technique used are converting to grayscale image, implementing sharpening filter and median filter. As for feature extraction, gray level co-occurrence matrix is used. Ensemble classification, a model in which better predictive performance is achieved through the incorporation of the outputs of multiple classification models into a good classification process. The developed prototype is using 60 images. This system was tested for accuracy by calculating the percentage of the entire application accuracy. The result showed that the classification of ensemble would yield accurate result with the highest percentage of accuracy which is 86.67%. The research will help to identify more forms of Adolescent Idiopathic Scoliosis with a lot of data for the future work of the project. To help physicians and surgeons, computer-aided software will be built in the future for Adolescent Idiopathic Scoliosis. 2020 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/31489/1/31489.pdf Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip. (2020) Degree thesis, thesis, Universiti Teknologi MARA, Cawangan Melaka. <http://terminalib.uitm.edu.my/31489.pdf>
spellingShingle Cartography
Instruments and machines
Electronic Computers. Computer Science
Mohd Hanip, Aisyah Afifah
Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip
title Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip
title_full Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip
title_fullStr Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip
title_full_unstemmed Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip
title_short Identification of Adolescent Idiopathic Scoliosis using image processing / Aisyah Afifah Mohd Hanip
title_sort identification of adolescent idiopathic scoliosis using image processing / aisyah afifah mohd hanip
topic Cartography
Instruments and machines
Electronic Computers. Computer Science
url https://ir.uitm.edu.my/id/eprint/31489/1/31489.pdf
https://ir.uitm.edu.my/id/eprint/31489/
url_provider http://ir.uitm.edu.my/