{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:08:09Z","timestamp":1743113289168,"version":"3.40.3"},"publisher-location":"Cham","reference-count":14,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031355097"},{"type":"electronic","value":"9783031355103"}],"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\/978-3-031-35510-3_11","type":"book-chapter","created":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T08:01:48Z","timestamp":1685520108000},"page":"99-109","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Fast Stroke Lesions Segmentation Based on\u00a0Parzen Estimation and\u00a0Non-uniform Bit Allocation in\u00a0Skull CT Images"],"prefix":"10.1007","author":[{"given":"Ald\u00edsio Gon\u00e7alves","family":"Medeiros","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucas","family":"de Oliveira Santos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pedro Pedrosa Rebou\u00e7as","family":"Filho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,6,1]]},"reference":[{"key":"11_CR1","doi-asserted-by":"crossref","unstructured":"Classifiers based on Bayes decision theory. In: Theodoridis, S., Koutroumbas, K. (eds.) Pattern Recognition, pp. 13 \u2013 89. Academic Press, Boston, 4th edn. (2009)","DOI":"10.1016\/B978-1-59749-272-0.50004-9"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Dunn, J.C.: A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters (1973)","DOI":"10.1080\/01969727308546046"},{"key":"11_CR3","series-title":"SpringerBriefs in Electrical and Computer Engineering","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1007\/978-3-319-15609-5_4","volume-title":"Radio Frequency Source Coding Made Easy","author":"S Faruque","year":"2015","unstructured":"Faruque, S.: Pulse code modulation (PCM). In: Radio Frequency Source Coding Made Easy. SECE, pp. 65\u201390. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-15609-5_4"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Han, T., et al.: Internet of medical things-based on deep learning techniques for segmentation of lung and stroke regions in CT scans. IEEE Access 8, 71117\u201371135 (2020)","DOI":"10.1109\/ACCESS.2020.2987932"},{"issue":"2","key":"11_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5121\/ijdkp.2015.5201","volume":"5","author":"M Hossin","year":"2015","unstructured":"Hossin, M., Sulaiman, M.: A review on evaluation metrics for data classification evaluations. Int. J. Data Mining Knowl. Manage. Process 5(2), 1 (2015)","journal-title":"Int. J. Data Mining Knowl. Manage. Process"},{"key":"11_CR6","unstructured":"K\u00f6rbes, A., Lotufo, R.: Analise de algoritmos da transformada watershed. In: 17th International Conference on Systems, Signals and Image Processing (2010)"},{"key":"11_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1007\/978-3-030-61380-8_41","volume-title":"Intelligent Systems","author":"AG Medeiros","year":"2020","unstructured":"Medeiros, A.G., Santos, L.O., Sarmento, R.M., Rebou\u00e7as, E.S., Filho, P.P.R.: New adaptive morphological geodesic active contour method for segmentation of hemorrhagic stroke in computed tomography image. In: Cerri, R., Prati, R.C. (eds.) BRACIS 2020. LNCS (LNAI), vol. 12320, pp. 604\u2013618. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-61380-8_41"},{"issue":"1","key":"11_CR8","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/0021-9991(88)90002-2","volume":"79","author":"S Osher","year":"1988","unstructured":"Osher, S., Sethian, J.A.: Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations. J. Comput. Phys. 79(1), 12\u201349 (1988)","journal-title":"J. Comput. Phys."},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Rebou\u00e7as, E.d.S., Braga, A.M., Sarmento, R.M., Marques, R.C., Rebou\u00e7as\u00a0Filho, P.P.: Level set based on brain radiological densities for stroke segmentation in CT images. In: IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), pp. 391\u2013396 (2017)","DOI":"10.1109\/CBMS.2017.172"},{"issue":"19","key":"11_CR10","doi-asserted-by":"publisher","first-page":"9265","DOI":"10.1007\/s00500-018-3491-4","volume":"23","author":"ES Rebou\u00e7as","year":"2018","unstructured":"Rebou\u00e7as, E.S., Marques, R.C.P., Braga, A.M., Oliveira, S.A.F., de Albuquerque, V.H.C., Rebou\u00e7as Filho, P.P.: New level set approach based on Parzen estimation for stroke segmentation in skull CT images. Soft. Comput. 23(19), 9265\u20139286 (2018). https:\/\/doi.org\/10.1007\/s00500-018-3491-4","journal-title":"Soft. Comput."},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"Rebou\u00e7as, E., Braga, A., Sarmento, R., Marques, R., Filho, P.P.: Level set based on brain radiological densities for stroke segmentation in CT images (2017)","DOI":"10.1109\/CBMS.2017.172"},{"key":"11_CR12","unstructured":"Ribeiro, M.A.B.: Estudo de um modelo de conversor a\/d com n\u00edveis de quantiza\u00e7\u00e3o configur\u00e1veis (2017)"},{"key":"11_CR13","unstructured":"Sethian, J.A.: Level set methods and fast marching methods: evolving interfaces in computational geometry, fluid mechanics, computer vision, and materials science, vol.\u00a03. Cambridge university press (1999)"},{"key":"11_CR14","doi-asserted-by":"crossref","unstructured":"de\u00a0Souza\u00a0Rebou\u00e7as, E., et al.: Level set approach based on Parzen window and floor of log for edge computing object segmentation in digital images. Appl. Soft Comput. 105, 107273 (2021)","DOI":"10.1016\/j.asoc.2021.107273"}],"container-title":["Lecture Notes in Networks and Systems","Intelligent Systems Design and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-35510-3_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T08:27:08Z","timestamp":1685521628000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-35510-3_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031355097","9783031355103"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-35510-3_11","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"1 June 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Systems Design and Applications","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":"12 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isda2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/isda22\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}