Image processing and algorithms for medical applications
Medicine was one of the earliest fields that applied digital image processing. Nowadays, medical image processing has been a necessary step for clinic us age, supporting physicians in decision making. This dissertation investigated the six main tasks: denoising, enhancement, registration, fusion,...
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| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Online Access: | https://hdl.handle.net/10356/161968 |
| _version_ | 1826114228917895168 |
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| author | Wang, Shangyu |
| author2 | Mohammed Yakoob Siyal |
| author_facet | Mohammed Yakoob Siyal Wang, Shangyu |
| author_sort | Wang, Shangyu |
| collection | NTU |
| description | Medicine was one of the earliest fields that applied digital image processing.
Nowadays, medical image processing has been a necessary step for clinic us age, supporting physicians in decision making. This dissertation investigated the
six main tasks: denoising, enhancement, registration, fusion, segmentation, clas sification in the sequence of application order in medical image processing in
the aspect of the entire computer-aided diagnosis procedure, and summarized
the development of methods in each task. Some representative algorithms in the
task of image denoising, enhancement, registration and segmentation are imple mented and compared. |
| first_indexed | 2024-10-01T03:35:45Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/161968 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:35:45Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1619682023-07-04T17:47:21Z Image processing and algorithms for medical applications Wang, Shangyu Mohammed Yakoob Siyal School of Electrical and Electronic Engineering EYAKOOB@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Medicine was one of the earliest fields that applied digital image processing. Nowadays, medical image processing has been a necessary step for clinic us age, supporting physicians in decision making. This dissertation investigated the six main tasks: denoising, enhancement, registration, fusion, segmentation, clas sification in the sequence of application order in medical image processing in the aspect of the entire computer-aided diagnosis procedure, and summarized the development of methods in each task. Some representative algorithms in the task of image denoising, enhancement, registration and segmentation are imple mented and compared. Master of Science (Signal Processing) 2022-09-27T08:58:35Z 2022-09-27T08:58:35Z 2022 Thesis-Master by Coursework Wang, S. (2022). Image processing and algorithms for medical applications. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/161968 https://hdl.handle.net/10356/161968 en application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Wang, Shangyu Image processing and algorithms for medical applications |
| title | Image processing and algorithms for medical applications |
| title_full | Image processing and algorithms for medical applications |
| title_fullStr | Image processing and algorithms for medical applications |
| title_full_unstemmed | Image processing and algorithms for medical applications |
| title_short | Image processing and algorithms for medical applications |
| title_sort | image processing and algorithms for medical applications |
| topic | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence |
| url | https://hdl.handle.net/10356/161968 |
| work_keys_str_mv | AT wangshangyu imageprocessingandalgorithmsformedicalapplications |