Malena Pérez-Sevilla, Fernando Rivas-Navazo, Pedro Latorre-Carmona, Darío Fernández-Zoppino
{"title":"Protocol for Converting DICOM Files to STL Models Using 3D Slicer and Ultimaker Cura.","authors":"Malena Pérez-Sevilla, Fernando Rivas-Navazo, Pedro Latorre-Carmona, Darío Fernández-Zoppino","doi":"10.3390/jpm15030118","DOIUrl":null,"url":null,"abstract":"<p><p><b>Background/Objectives</b>: 3D printing has become an invaluable tool in medicine, enabling the creation of precise anatomical models for surgical planning and medical education. This study presents a comprehensive protocol for converting DICOM files into three-dimensional models and their subsequent transformation into GCODE files ready for 3D printing. <b>Methods</b>: We employed the open-source software \"3D Slicer\" for the initial conversion of the DICOM files, capitalising on its robust capabilities in segmentation and medical image processing. An optimised workflow was developed for the precise and efficient conversion of medical images into STL models, ensuring high fidelity in anatomical structures. The protocol was validated through three case studies, achieving elevated structural fidelity based on deviation analysis between the STL models and the original DICOM data. Furthermore, the segmentation process preserved morphological accuracy within a narrow deviation range, ensuring the reliable replication of anatomical features for medical applications. Our protocol provides an effective and accessible approach to generating 3D anatomical models with enhanced accuracy and reproducibility. In later stages, we utilised the \"Ultimaker Cura\" software to generate customised GCODE files tailored to the specifications of the 3D printer. <b>Results</b>: Our protocol offers an effective, accessible, and more accurate solution for creating 3D anatomical models from DICOM images. Furthermore, the versatility of this approach allows for its adaptation to various 3D printers and materials, expanding its utility in the medical and scientific community. <b>Conclusions</b>: This study presents a robust and reproducible approach for converting medical data into physical three-dimensional objects, paving the way for a wide range of applications in personalised medicine and advanced clinical practice. The selection of sample datasets from the 3D Slicer repository ensures standardisation and reproducibility, allowing for independent validation of the proposed workflow without ethical or logistical constraints related to patient data access. However, we acknowledge that future work could expand upon this by incorporating real patient datasets and benchmarking the protocol against alternative segmentation methods and software packages to further assess performance across different clinical scenarios. Essentially, this protocol can be particularly characterised by its commitment to open-source software and low-cost solutions, making advanced 3D modelling accessible to a wider audience. By leveraging open-access tools such as \"3D Slicer\" and \"Ultimaker Cura\", we democratise the creation of anatomical models, ensuring that institutions with limited resources can also benefit from this technology, promoting innovation and inclusivity in medical sciences and education.</p>","PeriodicalId":16722,"journal":{"name":"Journal of Personalized Medicine","volume":"15 3","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11943244/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Personalized Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/jpm15030118","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background/Objectives: 3D printing has become an invaluable tool in medicine, enabling the creation of precise anatomical models for surgical planning and medical education. This study presents a comprehensive protocol for converting DICOM files into three-dimensional models and their subsequent transformation into GCODE files ready for 3D printing. Methods: We employed the open-source software "3D Slicer" for the initial conversion of the DICOM files, capitalising on its robust capabilities in segmentation and medical image processing. An optimised workflow was developed for the precise and efficient conversion of medical images into STL models, ensuring high fidelity in anatomical structures. The protocol was validated through three case studies, achieving elevated structural fidelity based on deviation analysis between the STL models and the original DICOM data. Furthermore, the segmentation process preserved morphological accuracy within a narrow deviation range, ensuring the reliable replication of anatomical features for medical applications. Our protocol provides an effective and accessible approach to generating 3D anatomical models with enhanced accuracy and reproducibility. In later stages, we utilised the "Ultimaker Cura" software to generate customised GCODE files tailored to the specifications of the 3D printer. Results: Our protocol offers an effective, accessible, and more accurate solution for creating 3D anatomical models from DICOM images. Furthermore, the versatility of this approach allows for its adaptation to various 3D printers and materials, expanding its utility in the medical and scientific community. Conclusions: This study presents a robust and reproducible approach for converting medical data into physical three-dimensional objects, paving the way for a wide range of applications in personalised medicine and advanced clinical practice. The selection of sample datasets from the 3D Slicer repository ensures standardisation and reproducibility, allowing for independent validation of the proposed workflow without ethical or logistical constraints related to patient data access. However, we acknowledge that future work could expand upon this by incorporating real patient datasets and benchmarking the protocol against alternative segmentation methods and software packages to further assess performance across different clinical scenarios. Essentially, this protocol can be particularly characterised by its commitment to open-source software and low-cost solutions, making advanced 3D modelling accessible to a wider audience. By leveraging open-access tools such as "3D Slicer" and "Ultimaker Cura", we democratise the creation of anatomical models, ensuring that institutions with limited resources can also benefit from this technology, promoting innovation and inclusivity in medical sciences and education.
期刊介绍:
Journal of Personalized Medicine (JPM; ISSN 2075-4426) is an international, open access journal aimed at bringing all aspects of personalized medicine to one platform. JPM publishes cutting edge, innovative preclinical and translational scientific research and technologies related to personalized medicine (e.g., pharmacogenomics/proteomics, systems biology). JPM recognizes that personalized medicine—the assessment of genetic, environmental and host factors that cause variability of individuals—is a challenging, transdisciplinary topic that requires discussions from a range of experts. For a comprehensive perspective of personalized medicine, JPM aims to integrate expertise from the molecular and translational sciences, therapeutics and diagnostics, as well as discussions of regulatory, social, ethical and policy aspects. We provide a forum to bring together academic and clinical researchers, biotechnology, diagnostic and pharmaceutical companies, health professionals, regulatory and ethical experts, and government and regulatory authorities.