{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T22:40:09Z","timestamp":1747089609728,"version":"3.40.5"},"publisher-location":"Cham","reference-count":36,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030764227"},{"type":"electronic","value":"9783030764234"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-76423-4_9","type":"book-chapter","created":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T07:03:58Z","timestamp":1620889438000},"page":"139-145","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A Heuristic-Based Decision Tree for Connected Components Labeling of 3D Volumes: Implementation and Reproducibility Notes"],"prefix":"10.1007","author":[{"given":"Federico","family":"Bolelli","sequence":"first","affiliation":[]},{"given":"Stefano","family":"Allegretti","sequence":"additional","affiliation":[]},{"given":"Costantino","family":"Grana","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,5,14]]},"reference":[{"key":"9_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1007\/978-3-642-16233-6_14","volume-title":"Facing the Multicore-Challenge","author":"A Abramov","year":"2010","unstructured":"Abramov, A., Kulvicius, T., W\u00f6rg\u00f6tter, F., Dellen, B.: Real-time image segmentation on a GPU. In: Keller, R., Kramer, D., Weiss, J.-P. (eds.) Facing the Multicore-Challenge. LNCS, vol. 6310, pp. 131\u2013142. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-16233-6_14"},{"doi-asserted-by":"crossref","unstructured":"Allegretti, S., Bolelli, F., Cancilla, M., Grana, C.: Optimizing GPU-based connected components labeling algorithms. In: 2018 IEEE International Conference on Image Processing, Applications and Systems (IPAS), pp. 175\u2013180. IEEE (2018)","key":"9_CR2","DOI":"10.1109\/IPAS.2018.8708900"},{"key":"9_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1007\/978-3-030-30645-8_25","volume-title":"Image Analysis and Processing \u2013 ICIAP 2019","author":"S Allegretti","year":"2019","unstructured":"Allegretti, S., Bolelli, F., Cancilla, M., Grana, C.: A block-based union-find algorithm to label connected components on GPUs. In: Ricci, E., Rota Bul\u00f2, S., Snoek, C., Lanz, O., Messelodi, S., Sebe, N. (eds.) ICIAP 2019. LNCS, vol. 11752, pp. 271\u2013281. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-30645-8_25"},{"key":"9_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1007\/978-3-030-29888-3_4","volume-title":"Computer Analysis of Images and Patterns","author":"S Allegretti","year":"2019","unstructured":"Allegretti, S., Bolelli, F., Cancilla, M., Pollastri, F., Canalini, L., Grana, C.: How does connected components labeling with decision trees perform on GPUs? In: Vento, M., Percannella, G. (eds.) CAIP 2019. LNCS, vol. 11678, pp. 39\u201351. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-29888-3_4"},{"key":"9_CR5","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1109\/TPDS.2019.2934683","volume":"31","author":"S Allegretti","year":"2019","unstructured":"Allegretti, S., Bolelli, F., Grana, C.: Optimized block-based algorithms to label connected components on GPUs. IEEE Trans. Parallel Distrib. Syst. 31, 423\u2013438 (2019)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"9_CR6","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1016\/j.procs.2012.09.009","volume":"11","author":"T Berka","year":"2012","unstructured":"Berka, T.: The generalized feed-forward loop motif: definition, detection and statistical significance. Procedia Comput. Sci. 11, 75\u201387 (2012)","journal-title":"Procedia Comput. Sci."},{"issue":"1","key":"9_CR7","first-page":"1999","volume":"29","author":"F Bolelli","year":"2019","unstructured":"Bolelli, F., Allegretti, S., Baraldi, L., Grana, C.: Spaghetti labeling: directed acyclic graphs for block-based connected components labeling. IEEE Trans. Image Process. 29(1), 1999\u20132012 (2019)","journal-title":"IEEE Trans. Image Process."},{"doi-asserted-by":"crossref","unstructured":"Bolelli, F., Allegretti, S., Grana, C.: One DAG to rule them all. IEEE Trans. Pattern Anal. Mach. Intell. 1\u201312 (2021)","key":"9_CR8","DOI":"10.1109\/TPAMI.2021.3055337"},{"doi-asserted-by":"crossref","unstructured":"Bolelli, F., Baraldi, L., Cancilla, M., Grana, C.: Connected components labeling on DRAGs. In: International Conference on Pattern Recognition, pp. 121\u2013126 (2018)","key":"9_CR9","DOI":"10.1109\/ICPR.2018.8545505"},{"key":"9_CR10","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/978-3-319-73165-0_15","volume-title":"Digital Libraries and Multimedia Archives","author":"F Bolelli","year":"2018","unstructured":"Bolelli, F., Borghi, G., Grana, C.: XDOCS: an application to index historical documents. In: Serra, G., Tasso, C. (eds.) IRCDL 2018. CCIS, vol. 806, pp. 151\u2013162. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-73165-0_15"},{"issue":"2","key":"9_CR11","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s11554-018-0756-1","volume":"17","author":"F Bolelli","year":"2018","unstructured":"Bolelli, F., Cancilla, M., Baraldi, L., Grana, C.: Toward reliable experiments on the performance of Connected Components Labeling algorithms. J. Real-Time Image Proc. 17(2), 229\u2013244 (2018). https:\/\/doi.org\/10.1007\/s11554-018-0756-1","journal-title":"J. Real-Time Image Proc."},{"key":"9_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1007\/978-3-319-68548-9_5","volume-title":"Image Analysis and Processing - ICIAP 2017","author":"F Bolelli","year":"2017","unstructured":"Bolelli, F., Cancilla, M., Grana, C.: Two more strategies to speed up connected components labeling algorithms. In: Battiato, S., Gallo, G., Schettini, R., Stanco, F. (eds.) ICIAP 2017. LNCS, vol. 10485, pp. 48\u201358. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-68548-9_5"},{"key":"9_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1007\/978-3-030-29888-3_8","volume-title":"Computer Analysis of Images and Patterns","author":"L Canalini","year":"2019","unstructured":"Canalini, L., Pollastri, F., Bolelli, F., Cancilla, M., Allegretti, S., Grana, C.: Skin lesion segmentation ensemble with diverse training strategies. In: Vento, M., Percannella, G. (eds.) CAIP 2019. LNCS, vol. 11678, pp. 89\u2013101. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-29888-3_8"},{"issue":"5","key":"9_CR14","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1007\/s11554-019-00912-8","volume":"17","author":"T Chabard\u00e8s","year":"2019","unstructured":"Chabard\u00e8s, T., Dokl\u00e1dal, P., Bilodeau, M.: A labeling algorithm based on a forest of decision trees. J. Real-Time Image Proc. 17(5), 1527\u20131545 (2019). https:\/\/doi.org\/10.1007\/s11554-019-00912-8","journal-title":"J. Real-Time Image Proc."},{"key":"9_CR15","doi-asserted-by":"publisher","first-page":"55731","DOI":"10.1109\/ACCESS.2018.2872452","volume":"6","author":"J Chen","year":"2018","unstructured":"Chen, J., Nonaka, K., Sankoh, H., Watanabe, R., Sabirin, H., Naito, S.: Efficient parallel connected component labeling with a coarse-to-fine strategy. IEEE Access 6, 55731\u201355740 (2018)","journal-title":"IEEE Access"},{"key":"9_CR16","volume-title":"A Discipline of Programming","author":"EW Dijkstra","year":"1976","unstructured":"Dijkstra, E.W.: A Discipline of Programming. Prentice-Hall, Englewood Cliffs (1976)"},{"unstructured":"Dinneen, M.J., Khosravani, M., Probert, A.: Using OpenCL for implementing simple parallel graph algorithms. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA) (2011)","key":"9_CR17"},{"unstructured":"Dubois, A., Charpillet, F.: Tracking mobile objects with several Kinects using HMMs and component labelling. In: Workshop Assistance and Service Robotics in a Human Environment, International Conference on Intelligent Robots and Systems, pp. 7\u201313 (2012)","key":"9_CR18"},{"key":"9_CR19","doi-asserted-by":"publisher","first-page":"24","DOI":"10.3389\/fninf.2014.00024","volume":"8","author":"A Eklund","year":"2014","unstructured":"Eklund, A., Dufort, P., Villani, M., LaConte, S.: BROCCOLI: software for fast fMRI analysis on many-core CPUs and GPUs. Front. Neuroinform. 8, 24 (2014)","journal-title":"Front. Neuroinform."},{"key":"9_CR20","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1007\/978-3-319-48680-2_38","volume-title":"Advanced Concepts for Intelligent Vision Systems","author":"C Grana","year":"2016","unstructured":"Grana, C., Baraldi, L., Bolelli, F.: Optimized connected components labeling with pixel prediction. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2016. LNCS, vol. 10016, pp. 431\u2013440. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-48680-2_38"},{"doi-asserted-by":"crossref","unstructured":"Grana, C., Bolelli, F., Baraldi, L., Vezzani, R.: YACCLAB - yet another connected components labeling benchmark. In: 2016 23rd International Conference on Pattern Recognition (ICPR), pp. 3109\u20133114. Springer (2016)","key":"9_CR21","DOI":"10.1109\/ICPR.2016.7900112"},{"doi-asserted-by":"crossref","unstructured":"He, L., Chao, Y., Suzuki, K.: A linear-time two-scan labeling algorithm. In: International Conference on Image Processing, vol. 5, pp. 241\u2013244 (2007)","key":"9_CR22","DOI":"10.1109\/ICIP.2007.4379810"},{"issue":"2","key":"9_CR23","doi-asserted-by":"publisher","first-page":"943","DOI":"10.1109\/TIP.2013.2289968","volume":"23","author":"L He","year":"2014","unstructured":"He, L., Zhao, X., Chao, Y., Suzuki, K.: Configuration-transition-based connected-component labeling. IEEE Trans. Image Process. 23(2), 943\u2013951 (2014)","journal-title":"IEEE Trans. Image Process."},{"key":"9_CR24","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.cpc.2015.04.015","volume":"194","author":"Y Komura","year":"2015","unstructured":"Komura, Y.: GPU-based cluster-labeling algorithm without the use of conventional iteration: application to the Swendsen-Wang multi-cluster spin flip algorithm. Comput. Phys. Commun. 194, 54\u201358 (2015)","journal-title":"Comput. Phys. Commun."},{"issue":"8","key":"9_CR25","doi-asserted-by":"publisher","first-page":"2039","DOI":"10.1109\/TPAMI.2013.63","volume":"35","author":"T Lelore","year":"2013","unstructured":"Lelore, T., Bouchara, F.: FAIR: a fast algorithm for document image restoration. IEEE Trans. Pattern Anal. Mach. Intell. 35(8), 2039\u20132048 (2013)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"doi-asserted-by":"crossref","unstructured":"Lucchi, A., Li, Y., Fua, P.: Learning for structured prediction using approximate subgradient descent with working sets. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1987\u20131994. IEEE (2013)","key":"9_CR26","DOI":"10.1109\/CVPR.2013.259"},{"issue":"12","key":"9_CR27","doi-asserted-by":"publisher","first-page":"2677","DOI":"10.1162\/jocn.2009.21407","volume":"22","author":"DS Marcus","year":"2010","unstructured":"Marcus, D.S., Fotenos, A.F., Csernansky, J.G., Morris, J.C., Buckner, R.L.: Open access series of imaging studies (OASIS): longitudinal MRI data in nondemented and demented older adults. J. Cognitive Neurosci. 22(12), 2677\u20132684 (2010)","journal-title":"J. Cognitive Neurosci."},{"issue":"2","key":"9_CR28","doi-asserted-by":"publisher","first-page":"292","DOI":"10.3390\/electronics9020292","volume":"9","author":"S Perri","year":"2020","unstructured":"Perri, S., Spagnolo, F., Corsonello, P.: A parallel connected component labeling architecture for heterogeneous systems-on-chip. Electronics 9(2), 292 (2020)","journal-title":"Electronics"},{"doi-asserted-by":"crossref","unstructured":"Pollastri, F., Bolelli, F., Paredes, R., Grana, C.: Improving skin lesion segmentation with generative adversarial networks. In: IEEE 31st International Symposium on Computer-Based Medical Systems (CBMS), pp. 442\u2013443. IEEE (2018)","key":"9_CR29","DOI":"10.1109\/CBMS.2018.00086"},{"issue":"21","key":"9_CR30","doi-asserted-by":"publisher","first-page":"15575","DOI":"10.1007\/s11042-019-7717-y","volume":"79","author":"F Pollastri","year":"2019","unstructured":"Pollastri, F., Bolelli, F., Paredes, R., Grana, C.: Augmenting data with GANs to segment melanoma skin lesions. Multimed. Tools Appl. 79(21), 15575\u201315592 (2019). https:\/\/doi.org\/10.1007\/s11042-019-7717-y","journal-title":"Multimed. Tools Appl."},{"issue":"4","key":"9_CR31","doi-asserted-by":"publisher","first-page":"471","DOI":"10.1145\/321356.321357","volume":"13","author":"A Rosenfeld","year":"1966","unstructured":"Rosenfeld, A., Pfaltz, J.L.: Sequential operations in digital picture processing. J. ACM 13(4), 471\u2013494 (1966)","journal-title":"J. ACM"},{"issue":"1","key":"9_CR32","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3390\/jlpea8010007","volume":"8","author":"F Spagnolo","year":"2018","unstructured":"Spagnolo, F., Frustaci, F., Perri, S., Corsonello, P.: An efficient connected component labeling architecture for embedded systems. J. Low Power Electron. Appl. 8(1), 7 (2018)","journal-title":"J. Low Power Electron. Appl."},{"doi-asserted-by":"crossref","unstructured":"S\u00f6chting, M., Allegretti, S., Bolelli, F., Grana, C.: A heuristic-based decision tree for connected components labeling of 3D volumes. In: 2020 25th International Conference on Pattern Recognition (ICPR). IEEE (2021)","key":"9_CR33","DOI":"10.1109\/ICPR48806.2021.9413096"},{"unstructured":"Wu, K., Otoo, E., Suzuki, K.: Two strategies to speed up connected component labeling algorithms. Technical report. LBNL-59102, Lawrence Berkeley National Laboratory (2005)","key":"9_CR34"},{"issue":"2","key":"9_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2352\/ISSN.2470-1173.2016.2.VIPC-240","volume":"2016","author":"S Zavalishin","year":"2016","unstructured":"Zavalishin, S., Safonov, I., Bekhtin, Y., Kurilin, I.: Block equivalence algorithm for labeling 2D and 3D images on GPU. Electron. Imaging 2016(2), 1\u20137 (2016)","journal-title":"Electron. Imaging"},{"key":"9_CR36","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/j.patcog.2019.02.022","volume":"91","author":"D Zhang","year":"2019","unstructured":"Zhang, D., Ma, H., Pan, L.: A gamma-signal-regulated connected components labeling algorithm. Pattern Recogn. 91, 281\u2013290 (2019)","journal-title":"Pattern Recogn."}],"container-title":["Lecture Notes in Computer Science","Reproducible Research in Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-76423-4_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,12]],"date-time":"2025-05-12T22:03:06Z","timestamp":1747087386000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-76423-4_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030764227","9783030764234"],"references-count":36,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-76423-4_9","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"14 May 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"RRPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Reproducible Research in Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 January 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 January 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"rrpr2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/rrpr2020.sciencesconf.org\/","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 (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":"18","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":"8","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":"5","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":"44% - 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":"2,66","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":"1,11","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)"}}]}}