{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T07:12:48Z","timestamp":1761808368889,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030453848"},{"type":"electronic","value":"9783030453855"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","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":[[2020]]},"DOI":"10.1007\/978-3-030-45385-5_63","type":"book-chapter","created":{"date-parts":[[2020,5,27]],"date-time":"2020-05-27T12:13:38Z","timestamp":1590581618000},"page":"705-715","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Brain MRI Modality Understanding: A Guide for Image Processing and Segmentation"],"prefix":"10.1007","author":[{"given":"Ayca","family":"Kirimtat","sequence":"first","affiliation":[]},{"given":"Ondrej","family":"Krejcar","sequence":"additional","affiliation":[]},{"given":"Ali","family":"Selamat","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,4,30]]},"reference":[{"key":"63_CR1","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"336","DOI":"10.1007\/978-3-030-14802-7_29","volume-title":"Intelligent Information and Database Systems","author":"J Kubicek","year":"2019","unstructured":"Kubicek, J., et al.: Design and analysis of LMMSE filter for MR image data. In: Nguyen, N.T., Gaol, F.L., Hong, T.-P., Trawi\u0144ski, B. (eds.) ACIIDS 2019. LNCS (LNAI), vol. 11432, pp. 336\u2013348. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-14802-7_29"},{"issue":"2","key":"63_CR2","doi-asserted-by":"publisher","first-page":"e50","DOI":"10.1111\/j.1552-6569.2009.00449.x","volume":"21","author":"JM Stankiewicz","year":"2011","unstructured":"Stankiewicz, J.M., et al.: Brain MRI lesion load at 1.5T and 3T versus clinical status in multiple sclerosis. J. Neuroimaging 21(2), e50\u2013e56 (2011). \nhttps:\/\/doi.org\/10.1111\/j.1552-6569.2009.00449.x","journal-title":"J. Neuroimaging"},{"issue":"3","key":"63_CR3","doi-asserted-by":"publisher","first-page":"261","DOI":"10.1007\/s10462-010-9155-0","volume":"33","author":"MA Balafar","year":"2010","unstructured":"Balafar, M.A., Ramli, A.R., Saripan, M.I., Mashohor, S.: Review of brain MRI image segmentation methods. Artif. Intell. Rev. 33(3), 261\u2013274 (2010). \nhttps:\/\/doi.org\/10.1007\/s10462-010-9155-0","journal-title":"Artif. Intell. Rev."},{"key":"63_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"711","DOI":"10.1007\/978-3-319-92058-0_68","volume-title":"Recent Trends and Future Technology in Applied Intelligence","author":"O Alpar","year":"2018","unstructured":"Alpar, O., Krejcar, O.: A comparative study on chrominance based methods in dorsal hand recognition: single image case. In: Mouhoub, M., Sadaoui, S., Ait Mohamed, O., Ali, M. (eds.) IEA\/AIE 2018. LNCS (LNAI), vol. 10868, pp. 711\u2013721. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-319-92058-0_68"},{"key":"63_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1007\/978-3-319-56148-6_35","volume-title":"Bioinformatics and Biomedical Engineering","author":"O Alpar","year":"2017","unstructured":"Alpar, O., Krejcar, O.: Quantization and equalization of pseudocolor images in hand thermography. In: Rojas, I., Ortu\u00f1o, F. (eds.) IWBBIO 2017. LNCS, vol. 10208, pp. 397\u2013407. Springer, Cham (2017). \nhttps:\/\/doi.org\/10.1007\/978-3-319-56148-6_35"},{"key":"63_CR6","doi-asserted-by":"publisher","unstructured":"Chang, P.-L., Teng, W.-G.: Exploiting the self-organizing map for medical image segmentation. Presented at the Twentieth IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007), Maribor, Slovenia (2007). \nhttps:\/\/doi.org\/10.1109\/CBMS.2007.48","DOI":"10.1109\/CBMS.2007.48"},{"key":"63_CR7","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1007\/978-3-662-49390-8_51","volume-title":"Intelligent Information and Database Systems","author":"T Marek","year":"2016","unstructured":"Marek, T., Krejcar, O., Selamat, A.: Possibilities for development and use of 3D applications on the android platform. In: Nguyen, N.T., Trawi\u0144ski, B., Fujita, H., Hong, T.-P. (eds.) ACIIDS 2016. LNCS (LNAI), vol. 9622, pp. 519\u2013529. Springer, Heidelberg (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-662-49390-8_51"},{"key":"63_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/978-3-319-40621-3_9","volume-title":"Augmented Reality, Virtual Reality, and Computer Graphics","author":"J Novotny","year":"2016","unstructured":"Novotny, J., Dvorak, J., Krejcar, O.: User based intelligent adaptation of five in a row game for android based on the data from the front camera. In: De Paolis, L.T., Mongelli, A. (eds.) AVR 2016. LNCS, vol. 9768, pp. 133\u2013149. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-40621-3_9"},{"key":"63_CR9","doi-asserted-by":"publisher","first-page":"672","DOI":"10.1109\/72.159057","volume":"3","author":"LO Hall","year":"1992","unstructured":"Hall, L.O., Bensaid, A.M., Clarke, L.P., Velthuizen, R.P., Silbiger, M.S., Bezdek, J.: A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain. IEEE Trans. Neural Netw. 3, 672\u2013682 (1992)","journal-title":"IEEE Trans. Neural Netw."},{"key":"63_CR10","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"324","DOI":"10.1007\/978-3-030-14802-7_28","volume-title":"Intelligent Information and Database Systems","author":"J Kubicek","year":"2019","unstructured":"Kubicek, J., et al.: Autonomous segmentation and modeling of brain pathological findings based on iterative segmentation from MR images. In: Nguyen, N.T., Gaol, F.L., Hong, T.-P., Trawi\u0144ski, B. (eds.) ACIIDS 2019. LNCS (LNAI), vol. 11432, pp. 324\u2013335. Springer, Cham (2019). \nhttps:\/\/doi.org\/10.1007\/978-3-030-14802-7_28"},{"key":"63_CR11","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/978-3-319-78759-6_23","volume-title":"Bioinformatics and Biomedical Engineering","author":"O Alpar","year":"2018","unstructured":"Alpar, O., Krejcar, O.: Thermal imaging for localization of anterior forearm subcutaneous veins. In: Rojas, I., Ortu\u00f1o, F. (eds.) IWBBIO 2018. LNCS, vol. 10814, pp. 243\u2013254. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-319-78759-6_23"},{"key":"63_CR12","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1007\/978-3-319-23485-4_33","volume-title":"Progress in Artificial Intelligence","author":"R Dolezal","year":"2015","unstructured":"Dolezal, R., et al.: Variable elimination approaches for data-noise reduction in 3D QSAR calculations. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds.) EPIA 2015. LNCS (LNAI), vol. 9273, pp. 313\u2013325. Springer, Cham (2015). \nhttps:\/\/doi.org\/10.1007\/978-3-319-23485-4_33"},{"issue":"7","key":"63_CR13","doi-asserted-by":"publisher","first-page":"1858","DOI":"10.1093\/brain\/awz144","volume":"142","author":"M Filippi","year":"2019","unstructured":"Filippi, M., et al.: Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines. Brain 142(7), 1858\u20131875 (2019). \nhttps:\/\/doi.org\/10.1093\/brain\/awz144","journal-title":"Brain"},{"key":"63_CR14","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1007\/978-3-319-75420-8_36","volume-title":"Intelligent Information and Database Systems","author":"T Samuel","year":"2018","unstructured":"Samuel, T., Assefa, D., Krejcar, O.: Framework for effective image processing to enhance tuberculosis diagnosis. In: Nguyen, N.T., Hoang, D.H., Hong, T.-P., Pham, H., Trawi\u0144ski, B. (eds.) ACIIDS 2018. LNCS (LNAI), vol. 10752, pp. 376\u2013384. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-319-75420-8_36"},{"key":"63_CR15","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1007\/978-3-319-05458-2_62","volume-title":"Intelligent Information and Database Systems","author":"M Kunes","year":"2014","unstructured":"Kunes, M., et al.: Imaging and evaluating method as part of endoscopical diagnostic approaches. In: Nguyen, N.T., Attachoo, B., Trawi\u0144ski, B., Somboonviwat, K. (eds.) ACIIDS 2014. LNCS (LNAI), vol. 8398, pp. 605\u2013614. Springer, Cham (2014). \nhttps:\/\/doi.org\/10.1007\/978-3-319-05458-2_62"},{"key":"63_CR16","doi-asserted-by":"publisher","unstructured":"Loizou, C.P., et al.: Brain image and lesions registration and 3D reconstruction in DICOM MRI images. In: 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), Thessaloniki, pp. 419\u2013422 (2017). \nhttps:\/\/doi.org\/10.1109\/CBMS.2017.53","DOI":"10.1109\/CBMS.2017.53"},{"key":"63_CR17","doi-asserted-by":"publisher","first-page":"104628","DOI":"10.1016\/j.dib.2019.104628","volume":"27","author":"J Qiao","year":"2019","unstructured":"Qiao, J., et al.: Data on MRI brain lesion segmentation using K-means and Gaussian mixture model-expectation maximization. Data Brief 27, 104628 (2019). \nhttps:\/\/doi.org\/10.1016\/j.dib.2019.104628","journal-title":"Data Brief"},{"key":"63_CR18","doi-asserted-by":"publisher","first-page":"102118","DOI":"10.1016\/j.nicl.2019.102118","volume":"25","author":"Y Xue","year":"2020","unstructured":"Xue, Y., et al.: A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images. NeuroImage Clin. 25, 102118 (2020). \nhttps:\/\/doi.org\/10.1016\/j.nicl.2019.102118","journal-title":"NeuroImage Clin."},{"issue":"1","key":"63_CR19","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1212\/WNL.55.1.55","volume":"55","author":"DC Mohr","year":"2000","unstructured":"Mohr, D.C., et al.: Psychological stress and the subsequent appearance of new brain MRI lesions in MS. Neurology 55(1), 55\u201361 (2000). \nhttps:\/\/doi.org\/10.1212\/WNL.55.1.55","journal-title":"Neurology"},{"key":"63_CR20","unstructured":"Preston, D.C.: Magnetic resonance imaging (MRI) of the brain and spine: basics. Magnetic Resonance Imaging (MRI) of the Brain and Spine: Basics (2006). \nhttps:\/\/casemed.case.edu\/clerkships\/neurology\/Web%20Neurorad\/MRI%20Basics.htm\n\n. Accessed 04 Jan 2020"},{"issue":"3","key":"63_CR21","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1007\/s10044-017-0597-8","volume":"20","author":"K Usman","year":"2017","unstructured":"Usman, K., Rajpoot, K.: Brain tumor classification from multi-modality MRI using wavelets and machine learning. Patt. Anal. Appl. 20(3), 871\u2013881 (2017). \nhttps:\/\/doi.org\/10.1007\/s10044-017-0597-8","journal-title":"Patt. Anal. Appl."},{"key":"63_CR22","doi-asserted-by":"publisher","unstructured":"Novoz\u00e1msk\u00fd, A., Flusser, J., Tachec\u00ed, I., Sul\u00edk, L., Bure\u0161, J., Krejcar, O.: Automatic blood detection in capsule endoscopy video. J. Biomed. Opt. 21(12) (2016). \nhttps:\/\/doi.org\/10.1117\/1.jbo.21.12.126007","DOI":"10.1117\/1.jbo.21.12.126007"},{"key":"63_CR23","doi-asserted-by":"publisher","first-page":"116507","DOI":"10.1016\/j.jns.2019.116507","volume":"407","author":"X Chen","year":"2019","unstructured":"Chen, X., et al.: A prediction model of brain edema after endovascular treatment in patients with acute ischemic stroke. J. Neurol. Sci. 407, 116507 (2019). \nhttps:\/\/doi.org\/10.1016\/j.jns.2019.116507","journal-title":"J. Neurol. Sci."},{"issue":"3","key":"63_CR24","doi-asserted-by":"publisher","first-page":"758","DOI":"10.1016\/j.jstrokecerebrovasdis.2017.10.010","volume":"27","author":"T Nakano","year":"2018","unstructured":"Nakano, T., et al.: Goreisan prevents brain edema after cerebral ischemic stroke by inhibiting Aquaporin 4 upregulation in mice. J. Stroke Cerebrovasc. Dis. 27(3), 758\u2013763 (2018). \nhttps:\/\/doi.org\/10.1016\/j.jstrokecerebrovasdis.2017.10.010","journal-title":"J. Stroke Cerebrovasc. Dis."}],"container-title":["Lecture Notes in Computer Science","Bioinformatics and Biomedical Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-45385-5_63","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,27]],"date-time":"2020-05-27T12:19:09Z","timestamp":1590581949000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-45385-5_63"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030453848","9783030453855"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-45385-5_63","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"30 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IWBBIO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Work-Conference on Bioinformatics and Biomedical Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 May 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 May 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwbbio2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/iwbbio.ugr.es\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}