{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T15:42:59Z","timestamp":1785426179244,"version":"3.56.0"},"reference-count":25,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,6,29]],"date-time":"2026-06-29T00:00:00Z","timestamp":1782691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013129","name":"Ministry of SMEs and Startups","doi-asserted-by":"publisher","award":["RS-2024-00488398"],"award-info":[{"award-number":["RS-2024-00488398"]}],"id":[{"id":"10.13039\/501100013129","id-type":"DOI","asserted-by":"publisher"}]},{"award":["RS-2024-00488398"],"award-info":[{"award-number":["RS-2024-00488398"]}],"id":[{"id":"https:\/\/ror.org\/022c4zk48","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Tomography"],"abstract":"<jats:p>Background\/Objectives: Virtual Bronchoscopic Navigation is used to guide bronchoscopes toward peripheral pulmonary lesions, but broad clinical and research adoption remains limited by the cost of proprietary software and by segmentation failures in small distal airways that can interrupt path planning. This study presents Virtual Bronchoscopic Pathfinder, an open-source, web-based system designed to provide automated airway segmentation, robust path generation, and browser-based three-dimensional visualization. Methods: The system integrates five components: a connectivity-aware deep learning model for pulmonary airway segmentation using Connectivity-Aware Surrogate and Local-Sensitive Distance modules; TotalSegmentator for automated tumor localization; a topology-preserving three-dimensional thinning algorithm implemented in C++ for centerline extraction; a bidirectional Dijkstra algorithm operating on a three-tier anatomical cost field with centerline, airway lumen, and parenchymal costs; and a zero-footprint visualization interface built on vtk.js with synchronized axial viewing and interactive volume rendering. VBP was validated on 306 thin-section CT series from 154 subjects in the public Lung-PET-CT-Dx dataset. Results: Among the 306 CT series, 33 series (10.8%) were excluded because of scanner-specific segmentation artifacts. In the remaining 273 anatomically valid series, the system successfully generated complete end-to-end navigation paths for all cases. The overall pipeline success rate was therefore 273 of 306 series (89.2%). The web-based interface was also confirmed to operate without client-side installation across desktop, laptop, and mobile device configurations. Conclusions: Virtual Bronchoscopic Pathfinder demonstrates that a reliable and accessible virtual bronchoscopic navigation workflow can be constructed entirely from open-source components. By combining connectivity-aware segmentation, cost-field path planning, and browser-based visualization, the system provides a practical foundation for imaging informatics research and future development of intra-procedural bronchoscopic guidance.<\/jats:p>","DOI":"10.3390\/tomography12070095","type":"journal-article","created":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T03:06:34Z","timestamp":1782875194000},"page":"95","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Virtual Bronchoscopic Pathfinder (VBP): An Open-Source Web-Based System for Airway Segmentation, Cost-Field Path Planning, and Cross-Device 3D Navigation"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7076-0884","authenticated-orcid":false,"given":"Young","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1478-5478","authenticated-orcid":false,"given":"Sunggyu","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Computer Science Engineering, College of IT, Kangwon National University, Chuncheon 24341, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-4233-5237","authenticated-orcid":false,"given":"Chulmin","family":"Park","sequence":"additional","affiliation":[{"name":"Growth Strategy Division, DOUZONEBIZON Co., Ltd., Chuncheon 24465, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0666-601X","authenticated-orcid":false,"given":"Woojin","family":"Park","sequence":"additional","affiliation":[{"name":"Department of Research and Development, ZIOVISION Co., Ltd., Chuncheon 24341, Republic of Korea"},{"name":"Department of Data Science, Graduate School, Kangwon National University, Chuncheon 24341, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5838-6925","authenticated-orcid":false,"given":"Doohee","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Research and Development, ZIOVISION Co., Ltd., Chuncheon 24341, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.ccm.2009.08.007","article-title":"Virtual Bronchoscopic Navigation","volume":"31","author":"Asano","year":"2010","journal-title":"Clin. Chest Med."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1016\/j.lungcan.2007.10.022","article-title":"Diagnosis of peripheral pulmonary lesions using a bronchoscope insertion guidance system combined with endobronchial ultrasonography with a guide sheath","volume":"60","author":"Asano","year":"2008","journal-title":"Lung Cancer"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"111","DOI":"10.2147\/LCTT.S98643","article-title":"Electromagnetic navigation bronchoscopy: Clinical utility in the diagnosis of lung cancer","volume":"7","author":"Seijo","year":"2016","journal-title":"Lung Cancer Targets Ther."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1109\/JBHI.2023.3324080","article-title":"Towards Connectivity-Aware Pulmonary Airway Segmentation","volume":"28","author":"Zhang","year":"2023","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2093","DOI":"10.1109\/TMI.2012.2209674","article-title":"Extraction of Airways from CT (EXACT\u201909)","volume":"31","author":"Lo","year":"2012","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"102957","DOI":"10.1016\/j.media.2023.102957","article-title":"Multi-Site, Multi-Domain Airway Tree Modeling","volume":"90","author":"Zhang","year":"2023","journal-title":"Med. Image Anal."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1109\/TMI.2020.3029013","article-title":"A CT-Based Automated Algorithm for Airway Segmentation Using Freeze-and-Grow Propagation and Deep Learning","volume":"40","author":"Nadeem","year":"2021","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2452","DOI":"10.1109\/TMI.2021.3078828","article-title":"Alleviating Class-Wise Gradient Imbalance for Pulmonary Airway Segmentation","volume":"40","author":"Zheng","year":"2021","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1603","DOI":"10.1109\/TMI.2021.3062280","article-title":"Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CT","volume":"40","author":"Qin","year":"2021","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Wang, A., Tam, T.C.C., Poon, H.M., Yu, K.C., and Lee, W.N. (2022). NaviAirway: A Bronchiole-Sensitive Deep Learning-Based Airway Segmentation Pipeline for Planning of Navigation Bronchoscopy. arXiv.","DOI":"10.36227\/techrxiv.19228296"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s11548-016-1447-7","article-title":"Pre-Clinical Validation of Virtual Bronchoscopy Using 3D Slicer","volume":"12","author":"Nardelli","year":"2017","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1049\/htl.2018.5074","article-title":"BronchoX: Bronchoscopy Exploration Software for Biopsy Intervention Planning","volume":"5","author":"Rosell","year":"2018","journal-title":"Healthc. Technol. Lett."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Lervik Bakeng, J.B., Hofstad, E.F., Solberg, O.V., Eiesland, J., Tangen, G.A., Amundsen, T., Lang\u00f8, T., Reinertsen, I., Selbekk, T., and Leira, H.O. (2019). Using the CustusX Toolkit to Create an Image Guided Bronchoscopy Application: Fraxinus. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0211772"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"982","DOI":"10.1109\/TMI.2009.2035813","article-title":"Robust 3-D Airway Tree Segmentation for Image-Guided Peripheral Bronchoscopy","volume":"29","author":"Graham","year":"2010","journal-title":"IEEE Trans. Med. Imaging"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1016\/j.chest.2020.08.2047","article-title":"Robotic Bronchoscopy for Peripheral Pulmonary Lesions: A Multicenter Pilot and Feasibility Study (BENEFIT)","volume":"159","author":"Chen","year":"2021","journal-title":"Chest"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e230024","DOI":"10.1148\/ryai.230024","article-title":"TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images","volume":"5","author":"Wasserthal","year":"2023","journal-title":"Radiol. Artif. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1006\/cgip.1994.1042","article-title":"Building Skeleton Models via 3-D Medial Surface Axis Thinning Algorithms","volume":"56","author":"Lee","year":"1994","journal-title":"CVGIP Graph. Model. Image Process."},{"key":"ref_18","unstructured":"Arganda-Carreras, I. (2025, August 12). Skeletonize3D (ImageJ Plugin). ImageJ\/Fiji Plugin. Version 2.1.1; ImageJ Version 1.54p. Available online: https:\/\/imagej.net\/plugins\/skeletonize3d."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/BF01386390","article-title":"A Note on Two Problems in Connexion with Graphs","volume":"1","author":"Dijkstra","year":"1959","journal-title":"Numer. Math."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Lee, D., Lee, K., Park, D.H., Moon, G., Park, I., Jeong, Y., Sung, K.Y., Choi, H.S., and Kim, Y. (2025). A Refined Approach to Segmenting and Quantifying Inter-Fracture Spaces in Facial Bone CT Imaging. Appl. Sci., 15.","DOI":"10.3390\/app15031539"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7005","DOI":"10.1038\/s41598-021-86546-y","article-title":"Clinical Application of Patient-Specific 3D Printing Brain Tumor Model Production System for Neurosurgery","volume":"11","author":"Dho","year":"2021","journal-title":"Sci. Rep."},{"key":"ref_22","unstructured":"Li, P., Wang, S., Li, T., Lu, J., HuangFu, Y., and Wang, D. (2025, December 22). A Large-Scale CT and PET\/CT Dataset for Lung Cancer Diagnosis (Lung-PET-CT-Dx) [Data Set]. The Cancer Imaging Archive, Available online: https:\/\/doi.org\/10.7937\/TCIA.2020.NNC2-0461."},{"key":"ref_23","unstructured":"Silversmith, W. (2026, February 07). dijkstra3d: Dijkstra\u2019s Shortest Path Algorithm for 3D Volumetric Images. GitHub Repository. Seung Lab, Princeton University. Available online: https:\/\/github.com\/seung-lab\/dijkstra3d."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hayat, M., Dhaliwal, A., Ud Din, M.M., Izhar, R., Nadeem, M., and Ahmad, N. (2025). Cross-Attention Patch Fusion for Few-Shot Colorectal Tissue Generation. 2025 5th International Conference on Digital Futures and Transformative Technologies (ICoDT2), IEEE.","DOI":"10.1109\/ICoDT269104.2025.11360745"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.cag.2014.02.003","article-title":"Parallel centerline extraction on the GPU","volume":"41","author":"Liu","year":"2014","journal-title":"Comput. 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