{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T10:33:33Z","timestamp":1681986813176},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2019,5,8]],"date-time":"2019-05-08T00:00:00Z","timestamp":1557273600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"the Training Program Foundation for 2016 Young Teacher from Shanghai Municipal Education Commission","award":["ZZsl15012"],"award-info":[{"award-number":["ZZsl15012"]}]},{"name":"the Cultivation Fund of the Scientific and Technical Innovation Project, USST","award":["1000302006"],"award-info":[{"award-number":["1000302006"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2019,8]]},"DOI":"10.1007\/s11517-019-01985-0","type":"journal-article","created":{"date-parts":[[2019,5,8]],"date-time":"2019-05-08T16:04:45Z","timestamp":1557331485000},"page":"1629-1643","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Dental hard tissue morphological segmentation with sparse representation-based classifier"],"prefix":"10.1007","volume":"57","author":[{"given":"Bin","family":"Cheng","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,5,8]]},"reference":[{"key":"1985_CR1","doi-asserted-by":"crossref","unstructured":"Rad AE, Rahim MS, Rehman A (eds) (2013) Evaluation of current dental radiographs segmentation approaches in computeraided applications. IETE Tech Rev 30(3):210\u2013222","DOI":"10.4103\/0256-4602.113498"},{"key":"1985_CR2","doi-asserted-by":"crossref","unstructured":"Michetti J, Georgelingurgel M, Mallet JP (eds) (2015) Influence of CBCT parameters on the output of an automatic edge-detection-based endodontic segmentation. Dentomaxillofac Radiol 44(8):20140413","DOI":"10.1259\/dmfr.20140413"},{"key":"1985_CR3","doi-asserted-by":"crossref","unstructured":"Razali MRM, Ahmad NS, Hassan R (eds) (2014) Sobel and canny edges segmentations for the dental age assessment. International Conference on Computer Assisted System in Health p 62\u201366","DOI":"10.1109\/CASH.2014.10"},{"key":"1985_CR4","unstructured":"Michetti J, Basarab A, Diemer F (eds) (2017) Comparison of an adaptive local thresholding method on CBCT and \u03bcCT endodontic images. Phys Med Biol 63(1):015020"},{"key":"1985_CR5","unstructured":"Shan DR, Gao FY 2010 The segmentation algorithm of dental CT images based on fuzzy maximum entropy and region growing. International Conference on Bioinformatics and Biomedical Technology p 74\u201378"},{"key":"1985_CR6","doi-asserted-by":"crossref","unstructured":"Arifin AZ, Indraswari R, Suciati N (eds) (2017) Region merging strategy using statistical analysis for interactive image segmentation on dental panoramic radiographs. International Review on Computers & Software 12(1):63","DOI":"10.15866\/irecos.v12i1.10825"},{"key":"1985_CR7","doi-asserted-by":"crossref","unstructured":"Setianingrum AH, Rini AS, Hakiem N eds. 2017. Image segmentation using the Otsu method in dental X-rays. International Conference on Informatics & Computing Biology p 1\u20136","DOI":"10.1109\/IAC.2017.8280611"},{"key":"1985_CR8","doi-asserted-by":"crossref","unstructured":"Lai YH, Lin PL 2008. Effective segmentation for dental X-ray images using texture-based fuzzy inference system. Advanced concepts for intelligent vision systems p 936\u2013947","DOI":"10.1007\/978-3-540-88458-3_85"},{"issue":"1","key":"1985_CR9","doi-asserted-by":"publisher","first-page":"3","DOI":"10.4103\/0971-6203.58777","volume":"35","author":"N Harma","year":"2010","unstructured":"Harma N, Aggarwal LM (2010) Automated medical image segmentation techniques. J Med Phys 35(1):3\u201314","journal-title":"J Med Phys"},{"key":"1985_CR10","unstructured":"Li H, Sun G, Sun H (eds) (2013) Watershed algorithm based on morphology for dental X-ray images segmentation. IEEE International Conference on Signal Processing p 877\u2013880"},{"key":"1985_CR11","doi-asserted-by":"crossref","unstructured":"Hussain S, Qi C, Asif MR, eds. 2016. A novel trigonometric energy functional for image segmentation in the presence of intensity in-homogeneity. IEEE international conference on multimedia and expo p 1\u20136","DOI":"10.1109\/ICME.2016.7552994"},{"key":"1985_CR12","unstructured":"Sepehrian M, Deylami AM, Zoroofi RA (2016) Individual teeth segmentation in CBCT and MSCT dental images using watershed. Biomed Eng p 1\u20136"},{"issue":"3","key":"1985_CR13","first-page":"643","volume":"32","author":"WK Tam","year":"2016","unstructured":"Tam WK, Lee HJ (2016) Improving tooth outline detection by active appearance model with intensity-diversification in intraoral radiographs. J Inf Sci Eng 32(3):643\u2013659","journal-title":"J Inf Sci Eng"},{"issue":"2","key":"1985_CR14","doi-asserted-by":"publisher","first-page":"221","DOI":"10.3722\/cadaps.2010.221-233","volume":"7","author":"T Kronfeld","year":"2010","unstructured":"Kronfeld T, Brunner D, Brunnett G (2010) Snake-based segmentation of teeth from virtual dental casts. Comput-Aided Des Applic 7(2):221\u2013233","journal-title":"Comput-Aided Des Applic"},{"key":"1985_CR15","doi-asserted-by":"crossref","unstructured":"Pandey P, Bhan A, Dutta MK 2017 Automatic image processing based dental image analysis using automatic Gaussian fitting energy and level sets. International Conference and Workshop on Bioinspired Intelligence p 1\u20135","DOI":"10.1109\/IWOBI.2017.7985529"},{"key":"1985_CR16","doi-asserted-by":"crossref","unstructured":"Pavaloiu IB, Goga N 2015 Neural network based edge detection for CBCT segmentation. E-Health and Bioengineering Conference p 1\u20134","DOI":"10.1109\/EHB.2015.7391414"},{"key":"1985_CR17","first-page":"161","volume":"44","author":"T Shimizu","year":"2004","unstructured":"Shimizu T, Tokumori K, Yoshiura K (2004) Automatic extraction of the tooth outline on the intra-oral radiograph using wavelet transforms. Shika Hoshasen 44:161\u2013168","journal-title":"Shika Hoshasen"},{"key":"1985_CR18","doi-asserted-by":"crossref","unstructured":"Streso K, Lagona F 2005 Hidden markov random field and frame modelling for TCA-image analysis. Mpidr Working Papers","DOI":"10.4054\/MPIDR-WP-2005-032"},{"key":"1985_CR19","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1016\/j.eswa.2015.11.001","volume":"46","author":"HS Le","year":"2016","unstructured":"Le HS, Tuan TM (2016) A cooperative semi-supervised fuzzy clustering framework for dental x-ray image segmentation. Expert Syst Appl 46:380\u2013393","journal-title":"Expert Syst Appl"},{"key":"1985_CR20","doi-asserted-by":"crossref","unstructured":"Prakash M, Gowsika U, eds. 2015. An identification of abnormalities in dental with support vector machine using image processing. Emerging Research in Computing, Information, Communication and Applications. Springer India p 29\u201340","DOI":"10.1007\/978-81-322-2550-8_4"},{"key":"1985_CR21","doi-asserted-by":"crossref","unstructured":"He H, He M, Han JVT, eds. 2017 Automatic detection of neovascularization in retinal images using extreme learning machine. Neurocomputing 277:218-227","DOI":"10.1016\/j.neucom.2017.03.093"},{"key":"1985_CR22","doi-asserted-by":"crossref","unstructured":"Maduskar P, Philipsen RH, Melendez J (eds) (2016) Automatic detection of pleural effusion in chest radiographs. Med Image Anal 28:29\u201340","DOI":"10.1016\/j.media.2015.09.004"},{"issue":"9","key":"1985_CR23","first-page":"411","volume":"4","author":"A Belghith","year":"2013","unstructured":"Belghith A, Balasubramanian M, Bowd C (2013) A unified framework for glaucoma progression detection using Heidelberg retina tomograph images. Comput Med Imaging Graph 4(9):411\u2013420","journal-title":"Comput Med Imaging Graph"},{"key":"1985_CR24","doi-asserted-by":"crossref","unstructured":"Wright J, Yang AY, Ganesh A (eds) (2008) Robust face recognition via sparse representation. IEEE Trans Pattern Anal Mach Intell 31(2):210\u2013227","DOI":"10.1109\/AFGR.2008.4813404"},{"key":"1985_CR25","unstructured":"Xi J, Wei W (2018) Dental hard tissue segmentation based on the modified marker-controlled watershed method. Application Research of Computers 35(12):3479-3483"},{"issue":"10","key":"1985_CR26","doi-asserted-by":"publisher","first-page":"6372","DOI":"10.1118\/1.4754304","volume":"39","author":"Y Gao","year":"2012","unstructured":"Gao Y, Liao S, Shen D (2012) Prostate segmentation by sparse representation based classification. Med Phys 39(10):6372\u20136387","journal-title":"Med Phys"},{"key":"1985_CR27","doi-asserted-by":"crossref","unstructured":"Zhang B, Karray F, Li Q (eds) (2012) Sparse representation classifier for microaneurysm detection and retinal blood vessel extraction. Inf Sci 200(1):78\u201390","DOI":"10.1016\/j.ins.2012.03.003"},{"issue":"1","key":"1985_CR28","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.neuroimage.2013.02.069","volume":"76","author":"T Tong","year":"2013","unstructured":"Tong T, Wolz R, Coupe P (2013) Segmentation of MR images via discriminative dictionary learning and sparse coding: application to hippocampus labeling. NeuroImage 76(1):11\u201323","journal-title":"NeuroImage"},{"key":"1985_CR29","doi-asserted-by":"crossref","unstructured":"Goswami G, Singh R, Vatsa M, eds. 2017. Kernel group sparse representation based classifier for multimodal biometrics. International Joint Conference on Neural Networks pp.2894\u20132901","DOI":"10.1109\/IJCNN.2017.7966214"},{"key":"1985_CR30","doi-asserted-by":"crossref","unstructured":"Rajyalakshmi U, Rao SK, Prasad KS 2017. Supervised classification of breast cancer malignancy using integrated modified marker controlled watershed approach. IEEE International Advance Computing Conference584\u2013589","DOI":"10.1109\/IACC.2017.0125"},{"key":"1985_CR31","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1007\/978-3-662-03939-7","volume-title":"Morphological image analysis: principles and applications","author":"P Soille","year":"1999","unstructured":"Soille P (1999) Morphological image analysis: principles and applications. Springer, Heidelberg, p 172\u2013173"},{"key":"1985_CR32","unstructured":"Van Rijsbergen, CJ (1979). Information retrieval (2nd ed.). Butterworth-Heinemann: Newton, MA, USA"},{"key":"1985_CR33","doi-asserted-by":"crossref","unstructured":"Sivaswamy J, Krishnadas SR, Joshi GD, eds. 2014. DrishtiGS: retinal image dataset for optic nerve head(ONH) segmentation. International symposium on biomedical imaging pp.53\u201356","DOI":"10.1109\/ISBI.2014.6867807"},{"key":"1985_CR34","unstructured":"Achanta R, Hemami SS, Estrada FJ (eds) (2009) IEEE Conference on Computer Vision and Pattern Recognition p 1597-1604"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-019-01985-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11517-019-01985-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-019-01985-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,6]],"date-time":"2020-05-06T23:26:59Z","timestamp":1588807619000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11517-019-01985-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,8]]},"references-count":34,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2019,8]]}},"alternative-id":["1985"],"URL":"https:\/\/doi.org\/10.1007\/s11517-019-01985-0","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,8]]},"assertion":[{"value":"28 July 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 May 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}