{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:55:09Z","timestamp":1740099309243,"version":"3.37.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030208660"},{"type":"electronic","value":"9783030208677"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-20867-7_41","type":"book-chapter","created":{"date-parts":[[2019,6,18]],"date-time":"2019-06-18T19:14:41Z","timestamp":1560885281000},"page":"532-543","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Combining Mathematical Morphology and the Hilbert Transform for Fully Automatic Nuclei Detection in Fluorescence Microscopy"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4114-1710","authenticated-orcid":false,"given":"Carl J.","family":"Nelson","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7949-723X","authenticated-orcid":false,"given":"Philip T. G.","family":"Jackson","sequence":"additional","affiliation":[]},{"given":"Boguslaw","family":"Obara","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,5,31]]},"reference":[{"issue":"2","key":"41_CR1","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1177\/1087057111420292","volume":"17","author":"MA Bray","year":"2012","unstructured":"Bray, M.A., Fraser, A.N., Hasaka, T.P., Carpenter, A.E.: Workflow and metrics for image quality control in large-scale high-content screens. J. Biomol. Screen. 17(2), 266\u2013274 (2012)","journal-title":"J. Biomol. Screen."},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Caicedo, J.C., et al.: Evaluation of deep learning strategies for nucleus segmentation in fluorescence images. bioRxiv (2018)","DOI":"10.1101\/335216"},{"issue":"10","key":"41_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/gb-2006-7-10-r100","volume":"7","author":"AE Carpenter","year":"2006","unstructured":"Carpenter, A.E., et al.: CellProfiler: image analysis software for identifying and quantifying cell phenotypes. Genome Biol. 7(10), 1\u201311 (2006)","journal-title":"Genome Biol."},{"issue":"11","key":"41_CR4","doi-asserted-by":"publisher","first-page":"3693","DOI":"10.1016\/j.patcog.2014.05.012","volume":"47","author":"M Fornaciari","year":"2014","unstructured":"Fornaciari, M., Prati, A., Cucchiara, R.: A fast and effective ellipse detector for embedded vision applications. Pattern Recogn. 47(11), 3693\u20133708 (2014)","journal-title":"Pattern Recogn."},{"key":"41_CR5","doi-asserted-by":"crossref","unstructured":"Gurcan, M.N., Pan, T., Shimada, H., Saltz, J.: Image analysis for neuroblastoma classification: segmentation of cell nuclei. In: International Conference of the IEEE Engineering in Medicine and Biology Society, pp. 4844\u20134847 (2006)","DOI":"10.1109\/IEMBS.2006.260837"},{"issue":"2","key":"41_CR6","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1111\/j.1469-8137.1912.tb05611.x","volume":"11","author":"P Jaccard","year":"1912","unstructured":"Jaccard, P.: The distribution of flora in the Alpine Zone. New Phytol. 11(2), 37\u201350 (1912)","journal-title":"New Phytol."},{"key":"41_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1007\/978-3-319-59063-9_7","volume-title":"Artificial Intelligence and Soft Computing","author":"PTG Jackson","year":"2017","unstructured":"Jackson, P.T.G., Obara, B.: Avoiding over-detection: towards combined object detection and counting. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2017. LNCS (LNAI), vol. 10245, pp. 75\u201385. Springer, Cham (2017). \n                      https:\/\/doi.org\/10.1007\/978-3-319-59063-9_7"},{"issue":"8","key":"41_CR8","doi-asserted-by":"publisher","first-page":"3665","DOI":"10.1109\/TIP.2017.2704660","volume":"26","author":"Q Jia","year":"2017","unstructured":"Jia, Q., Fan, X., Luo, Z., Song, L., Qiu, T.: A fast ellipse detector using projective invariant pruning. IEEE Trans. Image Process. 26(8), 3665\u20133679 (2017)","journal-title":"IEEE Trans. Image Process."},{"issue":"10","key":"41_CR9","doi-asserted-by":"publisher","first-page":"2600","DOI":"10.1109\/TBME.2010.2060336","volume":"57","author":"C Jung","year":"2010","unstructured":"Jung, C., Kim, C.: Segmenting clustered nuclei using H-minima transform-based marker extraction and contour parameterization. IEEE Trans. Biomed. Eng. 57(10), 2600\u20132604 (2010)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"41_CR10","doi-asserted-by":"crossref","unstructured":"Kong, J., et al.: Automated cell segmentation with 3D fluorescence microscopy images. In: IEEE International Symposium on Biomedical Imaging, pp. 1212\u20131215 (2015)","DOI":"10.1109\/ISBI.2015.7164091"},{"issue":"1","key":"41_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-2121-8-1","volume":"8","author":"G Li","year":"2007","unstructured":"Li, G., et al.: 3D cell nuclei segmentation based on gradient flow tracking. BMC Cell Biol. 8(1), 1\u201310 (2007)","journal-title":"BMC Cell Biol."},{"issue":"7","key":"41_CR12","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1038\/nmeth.2083","volume":"9","author":"V Ljosa","year":"2012","unstructured":"Ljosa, V., Sokolnicki, K.L., Carpenter, A.E.: Annotated high-throughput microscopy image sets for validation. Nat. Methods 9(7), 637\u2013637 (2012)","journal-title":"Nat. Methods"},{"issue":"1","key":"41_CR13","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1109\/JSTSP.2015.2505148","volume":"10","author":"K Nandy","year":"2016","unstructured":"Nandy, K., Chellappa, R., Kumar, A., Lockett, S.J.: Segmentation of nuclei from 3D microscopy images of tissue via graphcut optimization. IEEE J. Sel. Topics Signal Process. 10(1), 140\u2013150 (2016)","journal-title":"IEEE J. Sel. Topics Signal Process."},{"issue":"5","key":"41_CR14","doi-asserted-by":"publisher","first-page":"1449","DOI":"10.1016\/j.patcog.2012.11.007","volume":"46","author":"DK Prasad","year":"2013","unstructured":"Prasad, D.K., Leung, M.K.H., Quek, C.: ElliFit: an unconstrained, non-iterative, least squares based geometric ellipse fitting method. Pattern Recogn. 46(5), 1449\u20131465 (2013)","journal-title":"Pattern Recogn."},{"issue":"9","key":"41_CR15","doi-asserted-by":"publisher","first-page":"3204","DOI":"10.1016\/j.patcog.2012.02.014","volume":"45","author":"DK Prasad","year":"2012","unstructured":"Prasad, D.K., Leung, M.K., Cho, S.Y.: Edge curvature and convexity based ellipse detection method. Pattern Recogn. 45(9), 3204\u20133221 (2012)","journal-title":"Pattern Recogn."},{"key":"41_CR16","unstructured":"Ruusuvuori, P., Lehmussola, A., Selinummi, J., Rajala, T., Huttunen, H., Yli-Harja, O.: Benchmark set of synthetic images for validating cell image analysis algorithms. In: European Signal Processing Conference, pp. 1\u20135 (2008)"},{"key":"41_CR17","unstructured":"Xie, Y., Ji, Q.: A new efficient ellipse detection method. In: Proceedings of the 16th International Conference on Pattern Recognition, vol. 2, pp. 957\u2013960 (2002)"},{"issue":"3","key":"41_CR18","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1109\/JBHI.2016.2544245","volume":"21","author":"H Xu","year":"2016","unstructured":"Xu, H., Lu, C., Berendt, R., Jha, N., Mandal, M.: Automatic nuclei detection based on generalized Laplacian of Gaussian filters. IEEE J. Biomed. Health Inform. 21(3), 826\u2013837 (2016)","journal-title":"IEEE J. Biomed. Health Inform."},{"issue":"5","key":"41_CR19","doi-asserted-by":"publisher","first-page":"1729","DOI":"10.1109\/JBHI.2013.2297030","volume":"18","author":"H Xu","year":"2014","unstructured":"Xu, H., Lu, C., Mandal, M.: An efficient technique for nuclei segmentation based on ellipse descriptor analysis and improved seed detection algorithm. IEEE J. Biomed. Health Inform. 18(5), 1729\u20131741 (2014)","journal-title":"IEEE J. Biomed. Health Inform."}],"container-title":["Lecture Notes in Computer Science","Mathematical Morphology and Its Applications to Signal and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20867-7_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,6,18]],"date-time":"2019-06-18T19:17:07Z","timestamp":1560885427000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20867-7_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030208660","9783030208677"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20867-7_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"31 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISMM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Saarbr\u00fccken","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 July 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 July 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ismm2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ismm.uni-saarland.de\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"54","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"41","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"76% - 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"}},{"value":"3-4","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}