A Reproducible Workflow for Liver Volume Segmentation and 3D Model Generation Using Open-Source Tools

Badreddine Labakoum; Hamid El Malali; Amr Farhan; Azeddine Mouhsen; Aissam Lyazidi

doi:10.35882/jeeemi.v7i4.1086

Badreddine Labakoum Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco https://orcid.org/0009-0004-6414-3614
Hamid El Malali Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco https://orcid.org/0000-0002-5624-3816
Amr Farhan Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco; Sciences and Engineering of Biomedicals, Biophysics and Health Laboratory, Higher Institute of Health Sciences (ISSS), University Hassan 1st, Settat, Morocco https://orcid.org/0000-0003-1492-3837
Azeddine Mouhsen Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco https://orcid.org/0000-0003-3901-4736
Aissam Lyazidi Sciences and Engineering of Biomedicals, Biophysics and Health Laboratory, Higher Institute of Health Sciences (ISSS), University Hassan 1st, Settat, Morocco https://orcid.org/0000-0001-5899-0164

DOI: https://doi.org/10.35882/jeeemi.v7i4.1086

Keywords: Hepatic resection, Surgical simulation, 3D modelling, Image segmentation, Preoperative planning

Abstract

Complex liver resections related to hepatic tumors represent a major surgical challenge that requires precise preoperative planning supported by reliable three-dimensional (3D) anatomical models. In this context, accurate volumetric segmentation of the liver is a critical prerequisite to ensure the fidelity of printed models and to optimize surgical decision-making. This study compares different segmentation techniques integrated into open-source software to identify the most suitable approach for clinical application in resource-limited settings. Three semi-automatic methods, region growing, thresholding, and contour interpolation, were tested using the 3D Slicer platform and compared with a proprietary automatic method (Hepatic VCAR, GE Healthcare) and a manual segmentation reference, considered the gold standard. Ten anonymized abdominal CT volumes from the Medical Segmentation Decathlon dataset, encompassing various hepatic pathologies, were used to assess and compare the performance of each technique. Evaluation metrics included the Dice similarity coefficient (Dice), Hausdorff distance (HD), root mean square error (RMS), standard deviation (SD), and colorimetric surface discrepancy maps, enabling both quantitative and qualitative analysis of segmentation accuracy. Among the tested methods, the semi-automatic region growing approach demonstrated the highest agreement with manual segmentation (Dice = 0.935 ± 0.013; HD = 4.32 ± 0.48 mm), surpassing both other semi-automatic techniques and the automatic proprietary method. These results suggest that the region growing method implemented in 3D Slicer offers a reliable, accurate, and reproducible workflow for generating 3D liver models, particularly in surgical environments with limited access to advanced commercial solutions. The proposed methodology can potentially improve surgical planning, enhance training through realistic patient-specific models, and facilitate broader adoption of 3D printing in hepatobiliary surgery worldwide.

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Author Biographies

Badreddine Labakoum, Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco

was born on October 22, 1994, in Agadir, Morocco. He is a Ph.D. student and received his master’s degree in biomedical engineering: instrumentation and maintenance from the Faculty of Science and Technology Settat in 2017. His research areas include the applications and evaluation of 3D printing in the medical field and biomedical instrumentation. He works at the Laboratory of Energy-Materials-Instrumentation and Telecom (EMIT), Faculty of Sciences and Technology, Hassan 1st University, Morocco. BP: 577, road to Casablanca. Settat, Morocco. He can be contacted at b.labakoum@uhp.ac.ma

Hamid El Malali, Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco

was born in Errich- Midelt, Morocco. He holds a doctorate in Biomedical Engineering and Instrumentation Laboratory “RMI” in the Science and Technology Faculty, Hassan 1st University, Settat, Morocco. He holds a bachelor’s in physics from Sidi Mohammed ben Abdellah University, Fes in 1997, and a Master of Science and Technology in Biomedical Engineering and Instrumentation from Hassan 1st University, Settat in 2016. His research interests are computer vision, image processing, machine learning, and artificial intelligence. In 2003, he holds a diploma in computer science from the Regional Pedagogical Center of Fez. Currently, he is a professor of physics and medical imaging at Hassan First University, Settat Morocco. He can be contacted at email: h.elmalali@uhp.ac.ma.

Amr Farhan, Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco; Sciences and Engineering of Biomedicals, Biophysics and Health Laboratory, Higher Institute of Health Sciences (ISSS), University Hassan 1st, Settat, Morocco

is an Assistant Professor in Biomedical Engineering. He received the B.S. degree in Electronic Medical Engineering from Abou Bekr Belkaid Tlemcen University, Algeria, in 2011, and the M.S. degree in Biomedical Instrumentation from the same university in 2013. He obtained his Ph.D. degree in Physics and Engineering Science, specializing in Biomedical Engineering, from Hassan First University of Settat, Morocco, in 2025. His research interests include biomedical engineering, signal processing, 3D printing, machine learning, deep learning, and artificial intelligence their applications in the biomedical field. He can be contacted at a.farhan@uhp.ac.ma

Azeddine Mouhsen, Energy-Materials-Instrumentation and Telecom Laboratory (EMIT), Faculty of Science and Technology, University Hassan 1st, Settat, Morocco

was born on July 10, 1967 and is now a professor of Physics at Hassan First University, Morocco, since 1996. He holds a Ph.D. from Bordeaux I University (France) in 1995 and a thesis from Moulay Ismail University, Morocco, in 2001. He specializes in instrumentation and measurements, sensors, applied optics, energy transfer, and radiation-matter interactions. Azeddine Mouhsen has taught courses in physical sensors, chemical sensors, instrumentation, systems technology, digital electronics, and industrial data processing. He has published over 45 papers, and he is the co-inventor of one patent. He is the Director of the Laboratory of Energy-Materials-Instrumentation and Telecom (EMIT). He can be contacted at az.mouhsen@gmail.com

Aissam Lyazidi, Sciences and Engineering of Biomedicals, Biophysics and Health Laboratory, Higher Institute of Health Sciences (ISSS), University Hassan 1st, Settat, Morocco

Professor at the Higher Institute of Health Sciences, Hassan First University of Settat. He has published over 50 papers. He is the educational coordinator of the biomedical instrumentation and maintenance technologist program in the Higher Institute of Health Sciences, Hassan First University of Settat. His research areas include the field of biomedical engineering applied to clinical practice and medical training. He can be contacted at aissam.lyazidi@uhp.ac.ma

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