| Autor: |
Essamlali, Abdelhadi, Millot-Maysounabe, Vincent, Chartier, Marion, Salin, Grégoire, Becq, Aymeric, Arrivé, Lionel, Camus, Marine Duboc, Szewczyk, Jérôme, Claude, Isabelle |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
International Journal of Biomedical Engineering and Clinical Science, 2023, 9 (4), pp.66-74 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.11648/j.ijbecs.20230904.11 |
| Popis: |
This article presents an evaluation of biliary tract segmentation methods used for 3D reconstruction, which may be very usefull in various critical interventions, such as endoscopic retrograde cholangiopancreatography (ERCP), using the 3D Slicer software. This article provides an assessment of biliary tract segmentation techniques employed for 3D reconstruction, which can prove highly valuable in diverse critical procedures like endoscopic retrograde cholangiopancreatography (ERCP) through the utilization of 3D Slicer software. Three different methods, namely thresholding, flood filling, and region growing, were assessed in terms of their advantages and disadvantages. The study involved 10 patient cases and employed quantitative indices and qualitative evaluation to assess the segmentations obtained by the different segmentation methods against ground truth. The results indicate that the thresholding method is almost manual and time-consuming, while the flood filling method is semi-automatic and also time-consuming. Although both methods improve segmentation quality, they are not reproducible. Therefore, an automatic method based on region growing was developed to reduce segmentation time, albeit at the expense of quality. These findings highlight the pros and cons of different conventional segmentation methods and underscore the need to explore alternative approaches, such as deep learning, to optimize biliary tract segmentation in the context of ERCP. |
| Databáze: |
arXiv |
| Externí odkaz: |
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