{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:06:30Z","timestamp":1762430790293},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2013,10,8]],"date-time":"2013-10-08T00:00:00Z","timestamp":1381190400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Digit Imaging"],"published-print":{"date-parts":[[2014,2]]},"DOI":"10.1007\/s10278-013-9640-5","type":"journal-article","created":{"date-parts":[[2013,10,7]],"date-time":"2013-10-07T16:25:59Z","timestamp":1381163159000},"page":"133-144","source":"Crossref","is-referenced-by-count":34,"title":["Computer-Aided Segmentation System for Breast MRI Tumour using Modified Automatic Seeded Region Growing (BMRI-MASRG)"],"prefix":"10.1007","volume":"27","author":[{"given":"Ali Qusay","family":"Al-Faris","sequence":"first","affiliation":[]},{"given":"Umi Kalthum","family":"Ngah","sequence":"additional","affiliation":[]},{"given":"Nor Ashidi Mat","family":"Isa","sequence":"additional","affiliation":[]},{"given":"Ibrahim Lutfi","family":"Shuaib","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2013,10,8]]},"reference":[{"key":"9640_CR1","unstructured":"Gardiner I: CAD improves breast MRI workflow: increasing throughput while maintaining accuracy in breast MRI reads requires powerful workflow tools, 2010"},{"key":"9640_CR2","doi-asserted-by":"crossref","first-page":"51","DOI":"10.2214\/AJR.05.0269","volume":"187","author":"CD Lehman","year":"2006","unstructured":"Lehman CD, Peacock S, DeMartini WB, Chen X: A new automated software system to evaluate breast MR examinations: improved specificity without decreased sensitivity. Am J Roentgenol 187:51\u201356, 2006","journal-title":"Am J Roentgenol"},{"key":"9640_CR3","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/S1076-6332(03)80290-8","volume":"9","author":"L Li","year":"2002","unstructured":"Li L, Clark RA, Thomas JA: Computer-aided diagnosis of masses with full-field digital mammography. Acad Radiol 9:4\u201312, 2002","journal-title":"Acad Radiol"},{"key":"9640_CR4","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/4233.908389","volume":"5","author":"B Verma","year":"2001","unstructured":"Verma B, Zakos J: A computer-aided diagnosis system for digital mammograms based on fuzzy-neural and feature extraction techniques. IEEE Trans Inf Technol Biomed 5:46\u201354, 2001","journal-title":"IEEE Trans Inf Technol Biomed"},{"key":"9640_CR5","doi-asserted-by":"crossref","DOI":"10.1109\/INFRKM.2010.5466910","volume-title":"Empirical study of brain segmentation using particle swarm optimization","author":"S Ibrahim","year":"2010","unstructured":"Ibrahim S, Khalid NEA, Manaf M: Empirical study of brain segmentation using particle swarm optimization. Shah Alam, Selangor, 2010"},{"key":"9640_CR6","first-page":"157","volume":"4","author":"R Ganesan","year":"2009","unstructured":"Ganesan R, Radhakrishnan S: Segmentation of computed tomography brain images using genetic algorithm. Int J Soft Comput 4:157\u2013161, 2009","journal-title":"Int J Soft Comput"},{"issue":"2","key":"9640_CR7","first-page":"64","volume":"3","author":"R Hussain","year":"2011","unstructured":"Hussain R, Arif S, Sikander MA, Memon AR: Fuzzy clustering based malignant areas detection in noisy breast magnetic resonant (MR) images. Int J Acad Res 3(2):64, 2011","journal-title":"Int J Acad Res"},{"key":"9640_CR8","first-page":"483","volume":"15","author":"S Kannan","year":"2011","unstructured":"Kannan S, Sathya A, Ramathilagam S: Effective fuzzy clustering techniques for segmentation of breast MRI. Soft computing\u2014a fusion of foundations. Methodol Appl 15:483\u2013491, 2011","journal-title":"Methodol Appl"},{"key":"9640_CR9","doi-asserted-by":"crossref","unstructured":"Noor NM, Khalid NEA, Hassan R, Ibrahim S, Yassin IM: Adaptive Neuro-Fuzzy Inference System for Brain Abnormality Segmentation, 2010","DOI":"10.1109\/ICSGRC.2010.5562519"},{"key":"9640_CR10","doi-asserted-by":"crossref","first-page":"138","DOI":"10.4103\/2228-7477.95299","volume":"1","author":"R Azmi","year":"2011","unstructured":"Azmi R, Anbiaee R, Norozi N, Salehi L, Amirzadi A: IMPST: a new interactive self-training approach to segmentation suspicious lesions in breast MRI. J Med Signals Sens 1:138\u2013148, 2011","journal-title":"J Med Signals Sens"},{"key":"9640_CR11","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1109\/34.295913","volume":"16","author":"R Adams","year":"1994","unstructured":"Adams R, Bischof L: Seeded region growing. IEEE Trans Pattern Anal Machine Intell 16:641\u2013647, 1994","journal-title":"IEEE Trans Pattern Anal Machine Intell"},{"key":"9640_CR12","doi-asserted-by":"crossref","unstructured":"Khalid NEA, Ibrahim S, Manaf M, Ngah UK: Seed-Based Region Growing Study for Brain Abnormalities Segmentation. Proc. Information Technology (ITSim), 2010 International Symposium: City, 15\u201317 June 2010 Year","DOI":"10.1109\/ITSIM.2010.5561560"},{"key":"9640_CR13","first-page":"174","volume":"7","author":"S Ibrahim","year":"2011","unstructured":"Ibrahim S, Khalid NEA, Manaf M, Ngah UK: Particle swarm optimization vs seed-based region growing: brain abnormalities segmentation. Int J Artif Intell 7:174\u2013188, 2011","journal-title":"Int J Artif Intell"},{"key":"9640_CR14","unstructured":"Meinel LA: Development of computer-aided diagnostic system for breast MRI lesion classification. Dissertation. University of Iowa, Biomedical Engineering, PhD (Doctor of Philosophy), dissertation 2005"},{"issue":"1","key":"9640_CR15","first-page":"61","volume":"13","author":"NA Mat-Isa","year":"2005","unstructured":"Mat-Isa NA, Mashor MY, Othman NH: Seeded region growing features extraction algorithm; its potential use in improving screening for cervical cancer. Int J Comput Internet Manag 13(1):61\u201370, 2005","journal-title":"Int J Comput Internet Manag"},{"key":"9640_CR16","doi-asserted-by":"crossref","unstructured":"Wu J, Poehlman S, Noseworthy MD, Kamath MV: Texture feature based automated seeded region growing in abdominal MRI segmentation. Proc. BioMedical Engineering and Informatics BMEI 2008: City, 27\u201330 May 2008 Year","DOI":"10.1109\/BMEI.2008.352"},{"key":"9640_CR17","doi-asserted-by":"crossref","unstructured":"Shan J, Cheng HD, Wang Y: A novel automatic seed point selection algorithm for breast ultrasound images. Proc. Pattern Recognition, 2008 ICPR 2008 19th International Conference: City, 8\u201311 Dec. 2008 Year","DOI":"10.1109\/ICPR.2008.4761336"},{"key":"9640_CR18","unstructured":"Chun-yu N, Shu-fen L, Ming Q: Research on Removing Noise in Medical Image Based on Median Filter Method, 2009"},{"key":"9640_CR19","unstructured":"Li C, Xu C, Gui C, Fox MD: Level set evolution without re-initialization: a new variational formulation. Proc. Proceedings of the International Conference on Computer Vision and Pattern Recognition: City"},{"key":"9640_CR20","doi-asserted-by":"crossref","unstructured":"Al-Faris AQ, Ngah UK, Isa NAM, Shuaib IL: MRI breast skin-line segmentation and removal using integration method of level set active contour and morphological thinning algorithms. Journal of Medical Sciences, 2013","DOI":"10.3923\/jms.2012.286.291"},{"key":"9640_CR21","first-page":"879","volume":"14","author":"L Lam","year":"1992","unstructured":"Lam L, Seong-Whan L, Suen CY: Thinning methodologies\u2014a comprehensive survey. IEEE Trans Pattern Anal Mach Intell 14:879, 1992","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"9640_CR22","doi-asserted-by":"crossref","first-page":"642","DOI":"10.1109\/42.640755","volume":"16","author":"V Chalana","year":"1997","unstructured":"Chalana V, Kim Y: A methodology for evaluation of boundary detection algorithms on medical images. IEEE Trans Med Imaging 16:642\u2013652, 1997","journal-title":"IEEE Trans Med Imaging"},{"key":"9640_CR23","unstructured":"Fenster A, Chiu B: Evaluation of segmentation algorithms for medical imaging. Proc. Proceedings of IEEE 27th Annual Conference of the Engineering in Medicine and Biology Society: City, September 1\u20134 Year"},{"key":"9640_CR24","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1097\/00004424-198609000-00009","volume":"21","author":"CE Metz","year":"1986","unstructured":"Metz CE: ROC methodology in radiologic imaging. Invest Radiol 21:720\u2013733, 1986","journal-title":"Invest Radiol"},{"key":"9640_CR25","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1177\/0272989X8400400203","volume":"14","author":"BJ McNeil","year":"1984","unstructured":"McNeil BJ, Hanley JA: Statistical approaches to analysis of receiver operating characteristic (ROC) curves. Med Decis Making 14:137\u2013150, 1984","journal-title":"Med Decis Making"},{"key":"9640_CR26","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1007\/s11517-005-0021-1","volume":"44","author":"T Song","year":"2006","unstructured":"Song T, et al: A hybrid tissue segmentation approach for brain MR images. Med Biol Eng Comput 44:242, 2006","journal-title":"Med Biol Eng Comput"},{"issue":"10","key":"9640_CR27","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.compbiomed.2007.08.001","volume":"38","author":"G Ertas","year":"2008","unstructured":"Ertas G, G\u00fcl\u00e7\u00fcr HO, Osman O, Osman NU, Tunaci M, Dursun M: Breast MR segmentation and lesion detection with cellular neural networks and 3D template matching. Comput Biol Med 38(10):116\u2013126, 2008","journal-title":"Comput Biol Med"},{"key":"9640_CR28","unstructured":"US National Cancer Institute: reference image database to evaluate therapy response (RIDER) MRI breast, 2007"}],"container-title":["Journal of Digital Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-013-9640-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10278-013-9640-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10278-013-9640-5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,5]],"date-time":"2020-08-05T12:16:18Z","timestamp":1596629778000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10278-013-9640-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,10,8]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014,2]]}},"alternative-id":["9640"],"URL":"https:\/\/doi.org\/10.1007\/s10278-013-9640-5","relation":{},"ISSN":["0897-1889","1618-727X"],"issn-type":[{"value":"0897-1889","type":"print"},{"value":"1618-727X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,10,8]]}}}