3D Quantum Cuts for automatic segmentation of porous media in tomography images

Junaid Malik, Serkan Kiranyaz, Riyadh I. Al-Raoush, Olivier Monga, Patricia Garnier, Sebti Foufou, Abdelaziz Bouras, Alexandros Iosifidis, Moncef Gabbouj, Philippe C. Baveye

Tutkimustuotos: ArticleScientificvertaisarvioitu

9 Lataukset (Pure)


Binary segmentation of volumetric images of porous media is a crucial step towards gaining a deeper understanding of the factors governing biogeochemical processes at minute scales. Contemporary work primarily revolves around primitive techniques based on global or local adaptive thresholding that have known common drawbacks in image segmentation. Moreover, the absence of a unified benchmark prohibits quantitative evaluation, which further undermines the impact of existing methodologies. In this study, we tackle the issue on both fronts. First, by drawing parallels with natural image segmentation, we propose a novel, and automatic segmentation technique, 3D Quantum Cuts (QCuts-3D) grounded on a state-of-the-art spectral clustering technique. Secondly, we curate and present a publicly available dataset of 68 multiphase volumetric images of porous media with diverse solid geometries, along with voxel-wise ground truth annotations for each constituting phase. We provide comparative evaluations between QCuts-3D and the current state-of-the-art over this dataset across a variety of evaluation metrics. The proposed systematic approach achieves a 26% increase in AUROC (Area Under Receiver Operating Characteristics) while achieving a substantial reduction of the computational complexity over state-of-the-art competitors. Moreover, statistical analysis reveals that the proposed method exhibits significant robustness against the compositional variations of porous media.

JulkaisuComputers and Geosciences
Varhainen verkossa julkaisun päivämäärä2 jouluk. 2021
DOI - pysyväislinkit
TilaJulkaistu - helmik. 2022
OKM-julkaisutyyppiA1 Alkuperäisartikkeli


  • Jufo-taso 1

!!ASJC Scopus subject areas

  • Information Systems
  • Computers in Earth Sciences


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