{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T20:43:07Z","timestamp":1743021787241,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811667749"},{"type":"electronic","value":"9789811667756"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-16-6775-6_7","type":"book-chapter","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T20:02:30Z","timestamp":1703016150000},"page":"77-87","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Augmented Reality Applications for Image-Guided Robotic Interventions Using Deep Learning Algorithms"],"prefix":"10.1007","author":[{"given":"Jenna","family":"Seetohul","sequence":"first","affiliation":[]},{"given":"Mahmood","family":"Shafiee","sequence":"additional","affiliation":[]},{"given":"Konstantinos","family":"Sirlantzis","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,12,20]]},"reference":[{"key":"7_CR1","unstructured":"\u201cHolograms replacing cadavers in training for doctors\u201d. (Online) Available at: https:\/\/www.theguardian.com\/society\/2016\/nov\/17\/medical-trainers-look-to-virtual-reality-tech [Accessed on August 10, 2022]."},{"key":"7_CR2","doi-asserted-by":"publisher","unstructured":"Venkatesan, M.; Mohan, H.; Ryan, J.R.; Sch\u00fcrch, C.M.; Nolan, G.P.; Frakes, D.H.; Coskun, A.F. Virtual and augmented reality for biomedical applications. Cell Rep. Med. 2021, 2, 100348.https:\/\/doi.org\/10.1016\/j.xcrm.2021.100348.","DOI":"10.1016\/j.xcrm.2021.100348"},{"key":"7_CR3","doi-asserted-by":"crossref","unstructured":"Ronneberger, O., Fischer, P., & Brox, T. (2015, October). U-net: Convolutional networks for biomedical image segmentation. In\u00a0International Conference on Medical image computing and computer-assisted intervention\u00a0(pp. 234\u2013241). Springer, Cham.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"7_CR4","doi-asserted-by":"crossref","unstructured":"Qi, K., Yang, H., Li, C., Liu, Z., Wang, M., Liu, Q., & Wang, S. (2019, October). X-net: Brain stroke lesion segmentation based on depthwise separable convolution and long-range dependencies. In\u00a0International conference on medical image computing and computer-assisted intervention\u00a0(pp. 247\u2013255). Springer, Cham.","DOI":"10.1007\/978-3-030-32248-9_28"},{"key":"7_CR5","unstructured":"Jaderberg, M., Simonyan, K., & Zisserman, A. (2015). Spatial transformer networks.\u00a0Advances in neural information processing systems,\u00a028."},{"key":"7_CR6","unstructured":"Sokooti, H., de Vos, B., Berendsen, F., Ghafoorian, M., Yousefi, S., Lelieveldt, B. P., ... & Staring, M. (2019). 3D convolutional neural networks image registration based on efficient supervised learning from artificial deformations.\u00a0arXiv preprint arXiv:1908.10235."},{"key":"7_CR7","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.media.2018.11.010","volume":"52","author":"BD De Vos","year":"2019","unstructured":"De Vos, B. D., Berendsen, F. F., Viergever, M. A., Sokooti, H., Staring, M., & I\u0161gum, I. (2019). A deep learning framework for unsupervised affine and deformable image registration.\u00a0Medical image analysis,\u00a052, 128\u2013143.","journal-title":"Medical image analysis"},{"key":"7_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102139","volume":"72","author":"A Hering","year":"2021","unstructured":"Hering, A., H\u00e4ger, S., Moltz, J., Lessmann, N., Heldmann, S., & van Ginneken, B. (2021). CNN-based lung CT registration with multiple anatomical constraints.\u00a0Medical Image Analysis,\u00a072, 102139.","journal-title":"Medical Image Analysis"},{"issue":"8","key":"7_CR9","doi-asserted-by":"publisher","first-page":"1788","DOI":"10.1109\/TMI.2019.2897538","volume":"38","author":"G Balakrishnan","year":"2019","unstructured":"Balakrishnan, G., Zhao, A., Sabuncu, M. R., Guttag, J., & Dalca, A. V. (2019). VoxelMorph: a learning framework for deformable medical image registration.\u00a0IEEE transactions on medical imaging,\u00a038(8), 1788\u20131800.","journal-title":"IEEE transactions on medical imaging"},{"issue":"9","key":"7_CR10","doi-asserted-by":"publisher","first-page":"2246","DOI":"10.1109\/TMI.2021.3073986","volume":"40","author":"L Hansen","year":"2021","unstructured":"Hansen, L., & Heinrich, M. P. (2021). GraphRegNet: Deep graph regularisation networks on sparse keypoints for dense registration of 3D lung CTs.\u00a0IEEE Transactions on Medical Imaging,\u00a040(9), 2246\u20132257.","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"7_CR11","doi-asserted-by":"crossref","unstructured":"Fu, Y., Lei, Y., Wang, T., Curran, W. J., Liu, T., & Yang, X. (2020). Deep learning in medical image registration: a review.\u00a0Physics in Medicine & Biology,\u00a065(20), 20TR01.","DOI":"10.1088\/1361-6560\/ab843e"},{"issue":"1","key":"7_CR12","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/ab5da0","volume":"65","author":"Z Jiang","year":"2020","unstructured":"Jiang, Z., Yin, F. F., Ge, Y., & Ren, L. (2020). A multi-scale framework with unsupervised joint training of convolutional neural networks for pulmonary deformable image registration. Physics in Medicine & Biology, 65(1), 015011.","journal-title":"Physics in Medicine & Biology"},{"issue":"1","key":"7_CR13","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1007\/s11517-018-1861-9","volume":"57","author":"L Ma","year":"2019","unstructured":"Ma, L., Jiang, W., Zhang, B., Qu, X., Ning, G., Zhang, X., & Liao, H. (2019). Augmented reality surgical navigation with accurate CBCT-patient registration for dental implant placement.\u00a0Medical & biological engineering & computing,\u00a057(1), 47\u201357.","journal-title":"Medical & biological engineering & computing"},{"key":"7_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.autcon.2012.11.021","volume":"32","author":"X Wang","year":"2013","unstructured":"Wang, X., Kim, M. J., Love, P. E., & Kang, S. C. (2013). Augmented Reality in built environment: Classification and implications for future research. Automation in construction, 32, 1\u201313.","journal-title":"Automation in construction"},{"key":"7_CR15","doi-asserted-by":"crossref","unstructured":"Jiang, W., Ma, L., Zhang, B., Fan, Y., Qu, X., Zhang, X., & Liao, H. (2018). Evaluation of the 3D Augmented Reality\u2013Guided Intraoperative Positioning of Dental Implants in Edentulous Mandibular Models.\u00a0International Journal of Oral & Maxillofacial Implants,\u00a033(6).","DOI":"10.11607\/jomi.6638"}],"container-title":["Lecture Notes in Electrical Engineering","Medical Imaging and Computer-Aided Diagnosis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-6775-6_7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,4]],"date-time":"2025-03-04T18:26:28Z","timestamp":1741112788000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-6775-6_7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789811667749","9789811667756"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-6775-6_7","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"20 December 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICAD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Imaging and Computer-Aided Diagnosis","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 June 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 June 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"micad2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.micad.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}