{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T07:14:06Z","timestamp":1743059646521,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":20,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811941085"},{"type":"electronic","value":"9789811941092"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-19-4109-2_39","type":"book-chapter","created":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T14:38:26Z","timestamp":1659364706000},"page":"411-421","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Differential Evolution Algorithm for Medical Image Registration"],"prefix":"10.1007","author":[{"given":"Kangshun","family":"Li","sequence":"first","affiliation":[]},{"given":"Wenxiang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,1]]},"reference":[{"key":"39_CR1","unstructured":"Petra, A., VandenElsen, P.A.: Medical image matching-are view with classification. IEEE Trans. Biomed. Eng. 16(3), 26\u201329 (1993)"},{"key":"39_CR2","doi-asserted-by":"publisher","first-page":"554","DOI":"10.1097\/00004728-199707000-00007","volume":"21","author":"J West","year":"1997","unstructured":"West, J., Fitzpatrick, J.M., Wang, M.Y., et al.: Comparison and evaluation of retrospective intermodality brain image registration techniques. J. Comput. Assist. Tomogr. 21, 554\u2013566 (1997)","journal-title":"J. Comput. Assist. Tomogr."},{"key":"39_CR3","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1109\/42.730402","volume":"17","author":"JM Fitzpatrick","year":"1998","unstructured":"Fitzpatrick, J.M., Hill, D.L.G., Shyr, Y., et al.: Visual assessment of the accuracy of retrospective registration of MR and CT images of the brain. IEEE Trans. Med. Imaging 17, 571\u2013585 (1998)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"39_CR4","unstructured":"Zhu, X.: Research on multi-source image registration and fusion algorithm based on structural features. Dalian University of Technology (2017)"},{"issue":"2","key":"39_CR5","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91\u2013110 (2004)","journal-title":"Int. J. Comput. Vision"},{"key":"39_CR6","doi-asserted-by":"crossref","unstructured":"Bay, H.: SURF: speeded up robust features. In: Proceedings of ECCV, vol. 110(3), pp. 404\u2013417 (2006)","DOI":"10.1007\/11744023_32"},{"issue":"06","key":"39_CR7","first-page":"132","volume":"35","author":"M Shang","year":"2018","unstructured":"Shang, M., Wang, K.: An improved image registration algorithm based on Harris and SIFT operator. Microelectron. Comput. 35(06), 132\u2013134 (2018)","journal-title":"Microelectron. Comput."},{"key":"39_CR8","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1109\/34.121791","volume":"14","author":"PJ Besl","year":"1992","unstructured":"Besl, P.J., McKay, N.D.: A method for registration of 3-d shapes. IEEE Trans. Pattern Anal. Mach. Intell. 14, 239\u2013256 (1992)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"39_CR9","doi-asserted-by":"crossref","unstructured":"Ji, S., Ren, Y., Ji, Z., Liu, X., Hong, G.: An improved method for registration of point cloud. Optik \u2013 Int. J. Light Electron Optics 140, 451\u2013458 (2017)","DOI":"10.1016\/j.ijleo.2017.01.041"},{"issue":"4","key":"39_CR10","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn, R., Price, K.: Differential evolution \u2013 a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11(4), 341\u2013359 (1997)","journal-title":"J. Global Optim."},{"key":"39_CR11","unstructured":"Rusinkiewicz, S., Levoy, M.: Efficient Vatiants of the ICP Algorithm (2001)"},{"key":"39_CR12","doi-asserted-by":"crossref","unstructured":"Weik, S.: Registration of 3-D partial surface models using luminance and depth information. In: Proceedings of International Conference on Recent Advances in 3-D Digital Imaging and Modeling, pp. 93\u2013100 (1997)","DOI":"10.1109\/IM.1997.603853"},{"key":"39_CR13","doi-asserted-by":"crossref","unstructured":"Kamencay, P., Sinko, M., Hudec, R., Benco, M., Radil, R.: Improved feature point algorithm for 3D point cloud registration. In: Proceedings of the 2019 42nd International Conference on Telecommunications and Signal Processing (TSP), Budapest, Hungary, 1\u20133 July 2019, pp. 517\u2013520 (2019)","DOI":"10.1109\/TSP.2019.8769057"},{"key":"39_CR14","doi-asserted-by":"crossref","unstructured":"Masude, T., Sakaue, K., Yokoya, N.: Registration and integration of multiple range images for 3-D model construction. In: Proceedings of the 13th International Symposium on Pattern Recognition 1996, pp. 879\u2013883 (1996)","DOI":"10.1109\/ICPR.1996.546150"},{"key":"39_CR15","unstructured":"Chen, Y., Medioni, G.: Object modeling by registration of multiple range images. In: Proceedings of IEEE International Conference on Robotics and Autumation, pp. 2724\u20132729 (1991)"},{"issue":"2","key":"39_CR16","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/BF01427149","volume":"13","author":"A Zhang","year":"1994","unstructured":"Zhang, A.: Iterative point matching for registration of free-form curves and surface. Int. J. Comput. Vision 13(2), 119\u2013152 (1994)","journal-title":"Int. J. Comput. Vision"},{"key":"39_CR17","unstructured":"Greenspan, M., Yurick, M.: Approximate k-d tree search for efficient ICP. In: Proceeding of the Fourth International Conference on 3-D Digital Imaging and Modeling, pp. 442\u2013448 (2003)"},{"key":"39_CR18","doi-asserted-by":"crossref","unstructured":"Jiann-der, L., Shih-sen, H., Chung-hsien, H., et al.: An adaptive ICP registration for facial point data. In: Proceeding of the 18th International Conference on Pattern Recognition, pp. 703\u2013706 (2006)","DOI":"10.1109\/ICPR.2006.232"},{"key":"39_CR19","unstructured":"Cao, C.: Research on image registration method in surgical navigation and robot system. Shanghai University of applied technology (2020)"},{"key":"39_CR20","doi-asserted-by":"crossref","unstructured":"Malan, K.M., Engelbrecht, A.P.: Quantifying Ruggedness of Continuous Landscapes using Entropy. IEEE Congress on Evolutionary Computation (2009)","DOI":"10.1109\/CEC.2009.4983112"}],"container-title":["Communications in Computer and Information Science","Exploration of Novel Intelligent Optimization Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-19-4109-2_39","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,30]],"date-time":"2024-09-30T12:02:00Z","timestamp":1727697720000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-19-4109-2_39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811941085","9789811941092"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-981-19-4109-2_39","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"1 August 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISICA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Intelligence Computation and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Giangzhou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 November 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isica2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/gdstinfo.scau.edu.cn\/isica2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"99","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"48% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}