eess.IV - 2023-12-06

Bile Duct Segmentation Methods Under 3D Slicer Applied to ERCP: Advantages and Disadvantages

  • paper_url: http://arxiv.org/abs/2312.03356
  • repo_url: None
  • paper_authors: Abdelhadi Essamlali, Vincent Millot-Maysounabe, Marion Chartier, Grégoire Salin, Aymeric Becq, Lionel Arrivé, Marine Duboc Camus, Jérôme Szewczyk, Isabelle Claude
  • for: 这个研究旨在评估在3D重建中使用的胆囊道段化方法,以便在不同的关键手段中,如endorroscopic retrograde cholangiopancreatography(ERCP)中,实现更高的准确率和效率。
  • methods: 这篇文章评估了三种不同的段化方法,namely thresholding、flood filling和region growing,并对它们的优缺点进行评价。
  • results: 研究结果表明,阈值段化方法几乎是手动和时间consuming的,而洗涤填充方法是半自动的,但它们都不是可重复的。因此,一种基于区域生长的自动方法被开发出来,以减少段化时间,但是这会导致段化质量下降。这些结果highlight了不同的传统段化方法的优缺点,并强调了在ERCP中优化胆囊道段化的需要。
    Abstract 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.
    摘要