Implementation of MRI image processing
This proroject is focused on the processing of brain magnetic resonance imaging (MRI) images and identifying the tumour region. The method of identification is saliency, which is based on how the human eye looks at images and where the eye is drawn. There are several existing saliency algorithms, an...
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2020
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sg-ntu-dr.10356-1446462020-11-17T01:55:09Z Implementation of MRI image processing Chia, Dana Hui Yi Deepu Rajan School of Computer Science and Engineering ASDRajan@ntu.edu.sg Engineering::Computer science and engineering::Computer applications This proroject is focused on the processing of brain magnetic resonance imaging (MRI) images and identifying the tumour region. The method of identification is saliency, which is based on how the human eye looks at images and where the eye is drawn. There are several existing saliency algorithms, and the one implemented in this project aims to be more precise in its identification of the salient region. Images from the MICCAI 2015 Challenge dataset will be used as sample data, and MATLAB will be used to code the algorithm. The Image Processing Toolbox features will be used to display the images and results. After doing a comparison using a precision recall graph and ROC curves, the algorithm’s identification is shown to be more precise than those of its earlier counterparts. It shows great potential in locating tumour regions in the brain scans. It can therefore be used in the medical industry as a supplementary check, lest doctors miss the presence of a tumour in the brain scan image. Bachelor of Engineering (Computer Science) 2020-11-17T01:55:09Z 2020-11-17T01:55:09Z 2020 Final Year Project (FYP) https://hdl.handle.net/10356/144646 en SCSE19-0794 application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computer applications Chia, Dana Hui Yi Implementation of MRI image processing |
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This proroject is focused on the processing of brain magnetic resonance imaging (MRI) images and identifying the tumour region. The method of identification is saliency, which is based on how the human eye looks at images and where the eye is drawn. There are several existing saliency algorithms, and the one implemented in this project aims to be more precise in its identification of the salient region. Images from the MICCAI 2015 Challenge dataset will be used as sample data, and MATLAB will be used to code the algorithm. The Image Processing Toolbox features will be used to display the images and results. After doing a comparison using a precision recall graph and ROC curves, the algorithm’s identification is shown to be more precise than those of its earlier counterparts. It shows great potential in locating tumour regions in the brain scans. It can therefore be used in the medical industry as a supplementary check, lest doctors miss the presence of a tumour in the brain scan image. |
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Deepu Rajan |
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Deepu Rajan Chia, Dana Hui Yi |
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Final Year Project |
author |
Chia, Dana Hui Yi |
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Chia, Dana Hui Yi |
title |
Implementation of MRI image processing |
title_short |
Implementation of MRI image processing |
title_full |
Implementation of MRI image processing |
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Implementation of MRI image processing |
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Implementation of MRI image processing |
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implementation of mri image processing |
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Nanyang Technological University |
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2020 |
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https://hdl.handle.net/10356/144646 |
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