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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সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক: Moghbel, Mehrdad, Mashohor, Syamsiah, Mahmud, Rozi, Saripan, M. Iqbal
বিন্যাস: প্রবন্ধ
ভাষা:English
প্রকাশিত: Springer 2017
অনলাইন ব্যবহার করুন:http://psasir.upm.edu.my/id/eprint/62985/1/Review%20of%20liver%20segmentation%20and%20computer%20assisted.pdf
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spelling oai:psasir.upm.edu.my:62985 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
institution UPM IR
collection UPM IR
language English
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.
format Article
author Moghbel, Mehrdad
Mashohor, Syamsiah
Mahmud, Rozi
Saripan, M. Iqbal
spellingShingle Moghbel, Mehrdad
Mashohor, Syamsiah
Mahmud, Rozi
Saripan, M. Iqbal
Review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
author_facet Moghbel, Mehrdad
Mashohor, Syamsiah
Mahmud, Rozi
Saripan, M. Iqbal
author_sort Moghbel, Mehrdad
title 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_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_sort review of liver segmentation and computer assisted detection/diagnosis methods in computed tomography
publisher Springer
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/62985/1/Review%20of%20liver%20segmentation%20and%20computer%20assisted.pdf
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score 12.933938