Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
Computed tomography (CT) imaging remains the most utilized modality for liver-related cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature segmentation from CT data is a prerequisite for treatment planning and computer assisted detection/diagnosis systems. In...
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| Format: | Article |
| Language: | English |
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Springer
2017
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| Online Access: | http://psasir.upm.edu.my/id/eprint/62985/ http://psasir.upm.edu.my/id/eprint/62985/1/Review%20of%20liver%20segmentation%20and%20computer%20assisted.pdf |
| _version_ | 1848854704875896832 |
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| author | Moghbel, Mehrdad Mashohor, Syamsiah Mahmud, Rozi Saripan, M. Iqbal |
| author_facet | Moghbel, Mehrdad Mashohor, Syamsiah Mahmud, Rozi Saripan, M. Iqbal |
| author_sort | Moghbel, Mehrdad |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Computed tomography (CT) imaging remains the most utilized modality for liver-related cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature segmentation from CT data is a prerequisite for treatment planning and computer assisted detection/diagnosis systems. In this paper, we present a survey on liver, liver tumor and liver vasculature segmentation methods that are using CT images, recent methods presented in the literature are viewed and discussed along with positives, negatives and statistical performance of these methods. Liver computer assisted detection/diagnosis systems will also be discussed along with their limitations and possible ways of improvement. In this paper, we concluded that although there is still room for improvement, automatic liver segmentation methods have become comparable to human segmentation. However, the performance of liver tumor segmentation methods can be considered lower than expected in both automatic and semi-automatic methods. Furthermore, it can be seen that most computer assisted detection/diagnosis systems require manual segmentation of liver and liver tumors, limiting clinical applicability of these systems. Liver, liver tumor and liver vasculature segmentation is still an open problem since various weaknesses and drawbacks of these methods can still be addressed and improved especially in tumor and vasculature segmentation along with computer assisted detection/diagnosis systems. |
| first_indexed | 2025-11-15T11:14:06Z |
| format | Article |
| id | upm-62985 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T11:14:06Z |
| publishDate | 2017 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-629852018-09-28T10:26:34Z http://psasir.upm.edu.my/id/eprint/62985/ Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography Moghbel, Mehrdad Mashohor, Syamsiah Mahmud, Rozi Saripan, M. Iqbal Computed tomography (CT) imaging remains the most utilized modality for liver-related cancer screening and treatment monitoring purposes. Liver, liver tumor and liver vasculature segmentation from CT data is a prerequisite for treatment planning and computer assisted detection/diagnosis systems. In this paper, we present a survey on liver, liver tumor and liver vasculature segmentation methods that are using CT images, recent methods presented in the literature are viewed and discussed along with positives, negatives and statistical performance of these methods. Liver computer assisted detection/diagnosis systems will also be discussed along with their limitations and possible ways of improvement. In this paper, we concluded that although there is still room for improvement, automatic liver segmentation methods have become comparable to human segmentation. However, the performance of liver tumor segmentation methods can be considered lower than expected in both automatic and semi-automatic methods. Furthermore, it can be seen that most computer assisted detection/diagnosis systems require manual segmentation of liver and liver tumors, limiting clinical applicability of these systems. Liver, liver tumor and liver vasculature segmentation is still an open problem since various weaknesses and drawbacks of these methods can still be addressed and improved especially in tumor and vasculature segmentation along with computer assisted detection/diagnosis systems. Springer 2017-03-20 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/62985/1/Review%20of%20liver%20segmentation%20and%20computer%20assisted.pdf Moghbel, Mehrdad and Mashohor, Syamsiah and Mahmud, Rozi and Saripan, M. Iqbal (2017) Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography. Artificial Intelligence Review. pp. 1-41. ISSN 0269-2821; ESSN: 1573-7462 https://link.springer.com/content/pdf/10.1007%2Fs10462-017-9550-x.pdf 10.1007/s10462-017-9550-x |
| spellingShingle | Moghbel, Mehrdad Mashohor, Syamsiah Mahmud, Rozi Saripan, M. Iqbal Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| title | Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| title_full | Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| title_fullStr | Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| title_full_unstemmed | Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| title_short | Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| title_sort | review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography |
| url | http://psasir.upm.edu.my/id/eprint/62985/ http://psasir.upm.edu.my/id/eprint/62985/ http://psasir.upm.edu.my/id/eprint/62985/ http://psasir.upm.edu.my/id/eprint/62985/1/Review%20of%20liver%20segmentation%20and%20computer%20assisted.pdf |