Akshat Gotra, Lojan Sivakumaran, Gabriel Chartrand, Kim-Nhien Vu, Franck Vandenbroucke-Menu, Claude Kauffmann, Samuel Kadoury
, Benoit Gallix, Jacques A. de Guise and An Tang
Article (2017)
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Abstract
OBJECTIVES: Liver volumetry has emerged as an important tool in clinical practice. Liver volume is assessed primarily via organ segmentation of computed tomography (CT) and magnetic resonance imaging (MRI) images. The goal of this paper is to provide an accessible overview of liver segmentation targeted at radiologists and other healthcare professionals. METHODS: Using images from CT and MRI, this paper reviews the indications for liver segmentation, technical approaches used in segmentation software and the developing roles of liver segmentation in clinical practice. RESULTS: Liver segmentation for volumetric assessment is indicated prior to major hepatectomy, portal vein embolisation, associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) and transplant. Segmentation software can be categorised according to amount of user input involved: manual, semi-automated and fully automated. Manual segmentation is considered the "gold standard" in clinical practice and research, but is tedious and time-consuming. Increasingly automated segmentation approaches are more robust, but may suffer from certain segmentation pitfalls. Emerging applications of segmentation include surgical planning and integration with MRI-based biomarkers. CONCLUSIONS: Liver segmentation has multiple clinical applications and is expanding in scope. Clinicians can employ semi-automated or fully automated segmentation options to more efficiently integrate volumetry into clinical practice. TEACHING POINTS: * Liver volume is assessed via organ segmentation on CT and MRI examinations. * Liver segmentation is used for volume assessment prior to major hepatic procedures. * Segmentation approaches may be categorised according to the amount of user input involved. * Emerging applications include surgical planning and integration with MRI-based biomarkers.
Uncontrolled Keywords
| Subjects: |
1900 Biomedical engineering > 1900 Biomedical engineering 1900 Biomedical engineering > 1901 Biomedical technology |
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| Department: |
Department of Computer Engineering and Software Engineering Institut de génie biomédical |
| Funders: | Canadian Institute of Health Research Institute of Nutrition, Metabolism and Diabetes, Quebec Bio-Imaging Network, Centre de Recherche du Centre Hospitalier de l’Université de Montréal (CRCHUM), Fonds de recherche du Québec en Santé, MITACS industrial research award, Research Chair of Canada in 3D Imaging and Biomedical engineering award |
| Grant number: | CIHR-INMD no. 273738, QBIN no. 8436-0501, FRQS-ARQ no. 26993, IT02111 |
| PolyPublie URL: | https://publications.polymtl.ca/4900/ |
| Journal Title: | Insights into Imaging (vol. 8, no. 4) |
| Publisher: | Springer |
| DOI: | 10.1007/s13244-017-0558-1 |
| Official URL: | https://doi.org/10.1007/s13244-017-0558-1 |
| Date Deposited: | 17 Dec 2021 11:18 |
| Last Modified: | 08 Apr 2025 21:07 |
| Cite in APA 7: | Gotra, A., Sivakumaran, L., Chartrand, G., Vu, K.-N., Vandenbroucke-Menu, F., Kauffmann, C., Kadoury, S., Gallix, B., de Guise, J. A., & Tang, A. (2017). Liver segmentation: indications, techniques and future directions. Insights into Imaging, 8(4), 377-392. https://doi.org/10.1007/s13244-017-0558-1 |
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