ASM technique to detect spines in x-ray images
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Universiti Malaysia Perlis (UniMAP)
2016
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my.unimap-418132016-06-01T08:40:02Z ASM technique to detect spines in x-ray images Mohd Shuib, Sulaiman Salina Mohd Asi Spine Active shape models (ASM) Spine image Human spine OpenCV Access is limited to UniMAP community. The human spine regularly consists of 24 vertebrae. This project is about to detect the spines by implementing the Active Shape Models (ASM). The approaches ultilized by these technique is manual marking correspondences to make the training image. During this research, OpenCV libraries is the most appropriate material for object detection and image processing. Besides that, this project also conclude that better training shape of images can produce better output. This project used Stasm 4 software library integrated with OpenCV libraries. These configurations need to be test with sample given to make sure that it working properly. Even the training shape cannot detect the spines properly, but it still appears in better condition. In order to make this project success, the research need to improve their effort. Better understanding of OpenCv concept can helps a lot. 2016-06-01T08:40:02Z 2016-06-01T08:40:02Z 2015-06 Learning Object http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41813 en Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering |
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Spine Active shape models (ASM) Spine image Human spine OpenCV |
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Spine Active shape models (ASM) Spine image Human spine OpenCV Mohd Shuib, Sulaiman ASM technique to detect spines in x-ray images |
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Salina Mohd Asi |
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Salina Mohd Asi Mohd Shuib, Sulaiman |
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Learning Object |
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Mohd Shuib, Sulaiman |
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Mohd Shuib, Sulaiman |
title |
ASM technique to detect spines in x-ray images |
title_short |
ASM technique to detect spines in x-ray images |
title_full |
ASM technique to detect spines in x-ray images |
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ASM technique to detect spines in x-ray images |
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ASM technique to detect spines in x-ray images |
title_sort |
asm technique to detect spines in x-ray images |
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Universiti Malaysia Perlis (UniMAP) |
publishDate |
2016 |
url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41813 |
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1643799815223508992 |