Liver tumor volume estimation
In this study, two new methods to extract the liver tumor regions are developed. The first method involves a combination of thresholding, morphological operations and Fuzzy c-Means clustering techniques. Results show that tumor lesions, except the ones close to the liver brink, can be effectively ex...
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2008
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sg-ntu-dr.10356-48372023-07-04T17:39:28Z Liver tumor volume estimation Lu, Rui Marziliano, Pina School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics In this study, two new methods to extract the liver tumor regions are developed. The first method involves a combination of thresholding, morphological operations and Fuzzy c-Means clustering techniques. Results show that tumor lesions, except the ones close to the liver brink, can be effectively extracted from the CT images. The second method uses an active contour model to detect the boundaries of the tumors. In this method, the tumor region is extracted based on the minimization of an energy function and it yields a good description of the tumor boundary, while the initial contour has to be indicated by an operator manually. MASTER OF ENGINEERING (EEE) 2008-09-17T09:59:38Z 2008-09-17T09:59:38Z 2006 2006 Thesis Lu, R. (2006). Liver tumor volume estimation. Master’s thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/4837 10.32657/10356/4837 Nanyang Technological University application/pdf |
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Singapore Singapore |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics |
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DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Lu, Rui Liver tumor volume estimation |
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In this study, two new methods to extract the liver tumor regions are developed. The first method involves a combination of thresholding, morphological operations and Fuzzy c-Means clustering techniques. Results show that tumor lesions, except the ones close to the liver brink, can be effectively extracted from the CT images. The second method uses an active contour model to detect the boundaries of the tumors. In this method, the tumor region is extracted based on the minimization of an energy function and it yields a good description of the tumor boundary, while the initial contour has to be indicated by an operator manually. |
| author2 |
Marziliano, Pina |
| author_facet |
Marziliano, Pina Lu, Rui |
| format |
Theses and Dissertations |
| author |
Lu, Rui |
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Lu, Rui |
| title |
Liver tumor volume estimation |
| title_short |
Liver tumor volume estimation |
| title_full |
Liver tumor volume estimation |
| title_fullStr |
Liver tumor volume estimation |
| title_full_unstemmed |
Liver tumor volume estimation |
| title_sort |
liver tumor volume estimation |
| publishDate |
2008 |
| url |
https://hdl.handle.net/10356/4837 |
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1772828559245574144 |