{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:52:21Z","timestamp":1760151141090,"version":"build-2065373602"},"reference-count":38,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T00:00:00Z","timestamp":1645574400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001665","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["ANR-11-LABX-0004 (CAMI Labex)","ANR-14-CE17-0009 (DEPORRA2)","ANR-19-P3IA-0003 (MIAI@Grenoble Alpes)"],"award-info":[{"award-number":["ANR-11-LABX-0004 (CAMI Labex)","ANR-14-CE17-0009 (DEPORRA2)","ANR-19-P3IA-0003 (MIAI@Grenoble Alpes)"]}],"id":[{"id":"10.13039\/501100001665","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006367","name":"The Carnot Network","doi-asserted-by":"publisher","award":["Ressourcement Carnot LSI (Global Vision System for Laparoscopy project)"],"award-info":[{"award-number":["Ressourcement Carnot LSI (Global Vision System for Laparoscopy project)"]}],"id":[{"id":"10.13039\/501100006367","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Multi-camera systems were recently introduced into laparoscopy to increase the narrow field of view of the surgeon. The video streams are stitched together to create a panorama that is easier for the surgeon to comprehend. Multi-camera prototypes for laparoscopy use quite basic algorithms and have only been evaluated on simple laparoscopic scenarios. The more recent state-of-the-art algorithms, mainly designed for the smartphone industry, have not yet been evaluated in laparoscopic conditions. We developed a simulated environment to generate a dataset of multi-view images displaying a wide range of laparoscopic situations, which is adaptable to any multi-camera system. We evaluated classical and state-of-the-art image stitching techniques used in non-medical applications on this dataset, including one unsupervised deep learning approach. We show that classical techniques that use global homography fail to provide a clinically satisfactory rendering and that even the most recent techniques, despite providing high quality panorama images in non-medical situations, may suffer from poor alignment or severe distortions in simulated laparoscopic scenarios. We highlight the main advantages and flaws of each algorithm within a laparoscopic context, identify the main remaining challenges that are specific to laparoscopy, and propose methods to improve these approaches. We provide public access to the simulated environment and dataset.<\/jats:p>","DOI":"10.3390\/jimaging8030052","type":"journal-article","created":{"date-parts":[[2022,2,23]],"date-time":"2022-02-23T22:54:02Z","timestamp":1645656842000},"page":"52","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Qualitative Comparison of Image Stitching Algorithms for Multi-Camera Systems in Laparoscopy"],"prefix":"10.3390","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8761-2832","authenticated-orcid":false,"given":"Sylvain","family":"Guy","sequence":"first","affiliation":[{"name":"University Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7043-6166","authenticated-orcid":false,"given":"Jean-Loup","family":"Haberbusch","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8934-6793","authenticated-orcid":false,"given":"Emmanuel","family":"Promayon","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"St\u00e9phane","family":"Mancini","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, TIMA, 38031 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandrine","family":"Voros","sequence":"additional","affiliation":[{"name":"University Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, TIMC, 38000 Grenoble, France"},{"name":"University Grenoble Alpes, CNRS, UMR 5525, VetAgro Sup, Grenoble INP, INSERM, 38000 Grenoble, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1111\/j.1464-410X.2004.04558.x","article-title":"Laparoscopic radical nephrectomy for T1 renal cancer: The gold standard? A comparison of laparoscopic vs open nephrectomy","volume":"93","author":"Makhoul","year":"2004","journal-title":"BJU Int."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"75580T","DOI":"10.1117\/12.842417","article-title":"360 endoscopy using panomorph lens technology","volume":"Volume 7558","author":"Roulet","year":"2010","journal-title":"Endoscopic Microscopy V"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Kobayashi, E., Masamune, K., Sakuma, I., and Dohi, T. (2000, January 11\u201314). A Wide-Angle View Endoscope System Using Wedge Prisms. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, Pittsburgh, PA, USA.","DOI":"10.1007\/978-3-540-40899-4_68"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"17598","DOI":"10.1073\/pnas.1114746108","article-title":"Compact and flexible raster scanning multiphoton endoscope capable of imaging unstained tissue","volume":"108","author":"Rivera","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1117\/12.478049","article-title":"Microfabricated Optical Fiber with a Microlens That Produces Large Field-of-View Video-Rate Optical Beam Scanning for Microendoscopy Applications","volume":"Volume 4957","author":"Seibel","year":"2003","journal-title":"Optical Fibers and Sensors for Medical Applications III"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2403","DOI":"10.1007\/s00464-021-08369-2","article-title":"Improving vision for surgeons during laparoscopy: The Enhanced Laparoscopic Vision System (ELViS)","volume":"35","author":"Trilling","year":"2021","journal-title":"Surg. Endosc."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Tamadazte, B., Voros, S., Boschet, C., Cinquin, P., and Fouard, C. (2012). Augmented 3-d View for Laparoscopy Surgery. Workshop on Augmented Environments for Computer-Assisted Interventions, Springer.","DOI":"10.1007\/978-3-642-38085-3_12"},{"key":"ref_8","unstructured":"Trilling, B., Vijayan, S., Goupil, C., Kedisseh, E., Letouzey, A., Barraud, P., Faucheron, J., Fiard, G., and Voros, S. Enhanced Laparoscopic Vision Improves Detection of Intraoperative Adverse Events During Laparoscopy, IRBM, in press."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Kim, J.J., Watras, A., Liu, H., Zeng, Z., Greenberg, J.A., Heise, C.P., Hu, Y.H., and Jiang, H. (2018). Large-Field-of-View Visualization Utilizing Multiple Miniaturized Cameras for Laparoscopic Surgery. Micromachines, 9.","DOI":"10.3390\/mi9090431"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"204","DOI":"10.1007\/s40846-019-00503-9","article-title":"Designing a New Endoscope for Panoramic-View with Focus-Area 3D-Vision in Minimally Invasive Surgery","volume":"40","author":"Kim","year":"2020","journal-title":"J. Med. Biol. Eng."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1007\/s11548-018-1728-4","article-title":"Retrieval and registration of long-range overlapping frames for scalable mosaicking of in vivo fetoscopy","volume":"13","author":"Peter","year":"2018","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bano, S., Vasconcelos, F., Amo, M.T., Dwyer, G., Gruijthuijsen, C., Deprest, J., Ourselin, S., Vander Poorten, E., Vercauteren, T., and Stoyanov, D. (2019, January 13\u201317). Deep Sequential Mosaicking of Fetoscopic Videos. Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention, Shenzhen, China.","DOI":"10.1007\/978-3-030-32239-7_35"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1807","DOI":"10.1007\/s11548-020-02242-8","article-title":"Deep learning-based fetoscopic mosaicking for field-of-view expansion","volume":"15","author":"Bano","year":"2020","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"7831","DOI":"10.1109\/LRA.2021.3100938","article-title":"Globally Optimal Fetoscopic Mosaicking Based on Pose Graph Optimisation With Affine Constraints","volume":"6","author":"Li","year":"2021","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Aruna, K., Anil, V.S., Anand, A., Jaysankar, A., Venugopal, A., Nisha, K., and Sreelekha, G. (2021, January 1\u20133). Image Mosaicing for Neonatal Fundus Images. Proceedings of the 2021 8th International Conference on Smart Computing and Communications (ICSCC), Kochi, Kerala.","DOI":"10.1109\/ICSCC51209.2021.9528163"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1007\/s11263-006-0002-3","article-title":"Automatic panoramic image stitching using invariant features","volume":"74","author":"Brown","year":"2007","journal-title":"Int. J. Comput. Vis."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"Lowe","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Bay, H., Tuytelaars, T., and Van Gool, L. (2006, January 7\u201313). Surf: Speeded up Robust Features. Proceedings of the European Conference on Computer Vision, Graz, Austria.","DOI":"10.1007\/11744023_32"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1145\/882262.882264","article-title":"Graphcut textures: Image and video synthesis using graph cuts","volume":"22","author":"Kwatra","year":"2003","journal-title":"ACM Trans. Graph."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1145\/245.247","article-title":"A multiresolution spline with application to image mosaics","volume":"2","author":"Burt","year":"1983","journal-title":"ACM Trans. Graph."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Zaragoza, J., Chin, T.J., Brown, M.S., and Suter, D. (2013, January 23\u201328). As-Projective-as-Possible Image Stitching with Moving DLT. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Portland, OR, USA.","DOI":"10.1109\/CVPR.2013.303"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, F., and Liu, F. (2014, January 23\u201328). Parallax-Tolerant Image Stitching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Columbus, OH, USA.","DOI":"10.1109\/CVPR.2014.423"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lin, C.C., Pankanti, S.U., Natesan Ramamurthy, K., and Aravkin, A.Y. (2015, January 7\u201312). Adaptive as-Natural-as-Possible Image Stitching. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.","DOI":"10.1109\/CVPR.2015.7298719"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Chen, Y.S., and Chuang, Y.Y. (2016, January 11\u201314). Natural Image Stitching with the Global Similarity Prior. Proceedings of the European Conference on Computer Vision, Amsterdam, The Netherlands.","DOI":"10.1007\/978-3-319-46454-1_12"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1672","DOI":"10.1109\/TMM.2017.2777461","article-title":"Parallax-tolerant image stitching based on robust elastic warping","volume":"20","author":"Li","year":"2017","journal-title":"IEEE Trans. Multimed."},{"key":"ref_26","first-page":"1","article-title":"Content-preserving warps for 3D video stabilization","volume":"28","author":"Liu","year":"2009","journal-title":"ACM Trans. Graph."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1111\/cgf.12541","article-title":"Panoramic Video from Unstructured Camera Arrays","volume":"Volume 34","author":"Perazzi","year":"2015","journal-title":"Computer Graphics Forum"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"219","DOI":"10.1016\/j.neucom.2021.03.099","article-title":"Image stitching via deep homography estimation","volume":"450","author":"Zhao","year":"2021","journal-title":"Neurocomputing"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2346","DOI":"10.1109\/LRA.2018.2809549","article-title":"Unsupervised deep homography: A fast and robust homography estimation model","volume":"3","author":"Nguyen","year":"2018","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wang, C., Liu, S., Jia, L., Ye, N., Wang, J., Zhou, J., and Sun, J. (2020, January 23\u201328). Content-Aware Unsupervised Deep Homography Estimation. Proceedings of the European Conference on Computer Vision, Glasgow, UK.","DOI":"10.1007\/978-3-030-58452-8_38"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Shen, C., Ji, X., and Miao, C. (2019, January 4\u20139). Real-Time Image Stitching with Convolutional Neural Networks. Proceedings of the 2019 IEEE International Conference on Real-time Computing and Robotics (RCAR), Irkutsk, Russia.","DOI":"10.1109\/RCAR47638.2019.9044010"},{"key":"ref_32","unstructured":"Lai, W.S., Gallo, O., Gu, J., Sun, D., Yang, M.H., and Kautz, J. (2019). Video Stitching for Linear Camera Arrays. arXiv."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1109\/LSP.2021.3070525","article-title":"End-to-End Image Stitching Network via Multi-Homography Estimation","volume":"28","author":"Song","year":"2021","journal-title":"IEEE Signal Process. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"6184","DOI":"10.1109\/TIP.2021.3092828","article-title":"Unsupervised deep image stitching: Reconstructing stitched features to images","volume":"30","author":"Nie","year":"2021","journal-title":"IEEE Trans. Image Process."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Payan, Y. (2012). CamiTK: A Modular Framework Integrating Visualization, Image Processing and Biomechanical Modeling. Soft Tissue Biomechanical Modeling for Computer Assisted Surgery, Springer.","DOI":"10.1007\/978-3-642-29014-5"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2952","DOI":"10.1109\/TIP.2018.2808766","article-title":"A comparative study of algorithms for realtime panoramic video blending","volume":"27","author":"Zhu","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Gao, J., Kim, S.J., and Brown, M.S. (2011, January 20\u201325). Constructing Image Panoramas Using Dual-Homography Warping. Proceedings of the CVPR 2011, Colorado Springs, CO, USA.","DOI":"10.1109\/CVPR.2011.5995433"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1080\/21681163.2020.1835546","article-title":"VisionBlender: A tool to efficiently generate computer vision datasets for robotic surgery","volume":"9","author":"Cartucho","year":"2021","journal-title":"Comput. Methods Biomech. Biomed. Eng. Imaging Vis."}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/8\/3\/52\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:26:26Z","timestamp":1760135186000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/8\/3\/52"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,23]]},"references-count":38,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2022,3]]}},"alternative-id":["jimaging8030052"],"URL":"https:\/\/doi.org\/10.3390\/jimaging8030052","relation":{},"ISSN":["2313-433X"],"issn-type":[{"type":"electronic","value":"2313-433X"}],"subject":[],"published":{"date-parts":[[2022,2,23]]}}}