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Journal of Imaging Informatics in Medicine
Erschienen in: Journal of Digital Imaging 2/2020

19.08.2019

Survey on Liver Tumour Resection Planning System: Steps, Techniques, and Parameters

Erschienen in: Journal of Imaging Informatics in Medicine | Ausgabe 2/2020

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Abstract

Preoperative planning for liver surgical treatments is an essential planning tool that aids in reducing the risks of surgical resection. Based on the computed tomography (CT) images, the resection can be planned before the actual tumour resection surgery. The computer-aided system provides an overview of the spatial relationships of the liver organ and its internal structures, tumours, and vasculature. It also allows for an accurate calculation of the remaining liver volume after resection. The aim of this paper was to review the main stages of the computer-aided system that helps to evaluate the risk of resection during liver cancer surgical treatments. The computer-aided system assists with surgical planning by enabling physicians to get volumetric measurements and visualise the liver, tumours, and surrounding vasculature. In this paper, it is concluded that for accurate planning of tumour resections, the liver organ and its internal structures should be segmented to understand the clear spatial relationship between them, thus allowing for a safer resection. This paper presents the main proposed segmentation techniques for each stage in the computer-aided system, namely the liver organ, tumours, and vessels. From the reviewed methods, it has been found that instead of relying on a single specific technique, a combination of a group of techniques would give more accurate segmentation results. The extracted masks from the segmentation algorithms are fused together to give the surgeons the 3D visualisation tool to study the spatial relationships of the liver and to calculate the required resection planning parameters.
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Metadaten
Titel
Survey on Liver Tumour Resection Planning System: Steps, Techniques, and Parameters
Publikationsdatum
19.08.2019
Erschienen in
Journal of Imaging Informatics in Medicine / Ausgabe 2/2020
Print ISSN: 2948-2925
Elektronische ISSN: 2948-2933
DOI
https://doi.org/10.1007/s10278-019-00262-8

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