{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:16:30Z","timestamp":1740143790339,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2019,7,27]],"date-time":"2019-07-27T00:00:00Z","timestamp":1564185600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,7,27]],"date-time":"2019-07-27T00:00:00Z","timestamp":1564185600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61602221","61762050","61603415","61471101","41661083"],"award-info":[{"award-number":["61602221","61762050","61603415","61471101","41661083"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Science and Technology Research Project of Jiangxi Provincial Department of Education","award":["GJJ160333"],"award-info":[{"award-number":["GJJ160333"]}]},{"name":"the Natural Science Foundation of Jiangxi Province","award":["20171BAB212009"],"award-info":[{"award-number":["20171BAB212009"]}]},{"name":"the Project of Doctoral Foundation of Shenyang Aerospace University","award":["19YB01"],"award-info":[{"award-number":["19YB01"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s11517-019-02011-z","type":"journal-article","created":{"date-parts":[[2019,7,27]],"date-time":"2019-07-27T09:02:31Z","timestamp":1564218151000},"page":"2055-2067","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Adaptive weighted locality-constrained sparse coding for glaucoma diagnosis"],"prefix":"10.1007","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5931-3197","authenticated-orcid":false,"given":"Wei","family":"Zhou","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yugen","family":"Yi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jining","family":"Bao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenle","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,7,27]]},"reference":[{"key":"2011_CR1","doi-asserted-by":"crossref","unstructured":"Xu Y et al (2013) Efficient reconstruction-based optic cup localization for glaucoma screening. In: International conference on medical image computing and computer-assisted intervention. Springer, Berlin, Heidelberg, pp 445\u2013452","DOI":"10.1007\/978-3-642-40760-4_56"},{"key":"2011_CR2","doi-asserted-by":"crossref","unstructured":"Chakravarty A, Sivaswamy J (2016) Glaucoma classification with a fusion of segmentation and image-based features. In: 2016 IEEE 13th international symposium on biomedical imaging (ISBI). IEEE, pp 689\u2013692","DOI":"10.1109\/ISBI.2016.7493360"},{"issue":"6","key":"2011_CR3","doi-asserted-by":"publisher","first-page":"1019","DOI":"10.1109\/TMI.2013.2247770","volume":"32","author":"J Cheng","year":"2013","unstructured":"Cheng J, Liu J, Xu Y, Yin F, Wong DWK, Tan NM, Tao D, Cheng CY, Aung T, Wong TY (2013) Superpixel classification based optic disc and optic cup segmentation for glaucoma screening. IEEE Trans Med Imaging 32(6):1019\u20131032","journal-title":"IEEE Trans Med Imaging"},{"key":"2011_CR4","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.eswa.2018.06.010","volume":"110","author":"V dos Santos Ferreira Marcos","year":"2018","unstructured":"dos Santos Ferreira Marcos V et al (2018) Convolutional neural network and texture descriptor-based automatic detection and diagnosis of glaucoma. Expert Syst Appl 110:250\u2013263","journal-title":"Expert Syst Appl"},{"key":"2011_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TMI.2019.2899910","volume":"99","author":"S Wang","year":"2019","unstructured":"Wang S, Yu L, Yang X, Fu CW, Heng PA (2019) Patch-based output space adversarial learning for joint optic disc and cup segmentation. IEEE Trans Med Imaging 99:1\u20131. https:\/\/doi.org\/10.1109\/TMI.2019.2899910","journal-title":"IEEE Trans Med Imaging"},{"key":"2011_CR6","doi-asserted-by":"crossref","unstructured":"Wong DWK et al (2009) Intelligent fusion of cup-to-disc ratio determination methods for glaucoma detection in ARGALI. In: Engineering in medicine and biology society, 2009. EMBC 2009. Annual International Conference of the IEEE. IEEE, pp 5777\u20135780","DOI":"10.1109\/IEMBS.2009.5332534"},{"key":"2011_CR7","doi-asserted-by":"crossref","unstructured":"Xu Y et al (2011) Sliding window and regression based cup detection in digital fundus images for glaucoma diagnosis. In: International conference on medical image computing and computer-assisted intervention. Springer, Berlin, Heidelberg, pp 1\u20138","DOI":"10.1007\/978-3-642-23626-6_1"},{"key":"2011_CR8","doi-asserted-by":"crossref","unstructured":"Damon WWK et al (2012) Automatic detection of the optic cup using vessel kinking in digital retinal fundus images. In: 2012 9th IEEE international symposium on biomedical imaging (ISBI). IEEE, pp 1647\u20131650","DOI":"10.1109\/ISBI.2012.6235893"},{"issue":"5","key":"2011_CR9","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1109\/TBME.2015.2389234","volume":"62","author":"J Cheng","year":"2015","unstructured":"Cheng J, Yin F, Wong DWK, Tao D, Liu J (2015) Sparse dissimilarity-constrained coding for glaucoma screening. IEEE Trans Biomed Eng 62(5):1395\u20131403","journal-title":"IEEE Trans Biomed Eng"},{"key":"2011_CR10","doi-asserted-by":"crossref","unstructured":"Wang J et al (2010) Locality-constrained linear coding for image classification. In: 2010 IEEE conference on computer vision and pattern recognition (CVPR). IEEE, pp 3360\u20133367","DOI":"10.1109\/CVPR.2010.5540018"},{"key":"2011_CR11","doi-asserted-by":"publisher","first-page":"2760","DOI":"10.1109\/TIP.2015.2425545","volume":"24","author":"X Fang","year":"2015","unstructured":"Fang X et al (2015) Learning a nonnegative sparse graph for linear regression. IEEE Trans Image Process 24:2760\u20132771","journal-title":"IEEE Trans Image Process"},{"key":"2011_CR12","doi-asserted-by":"publisher","first-page":"1548","DOI":"10.1109\/TPAMI.2010.231","volume":"33","author":"D Cai","year":"2011","unstructured":"Cai D et al (2011) Graph regularized nonnegative matrix factorization for data representation. IEEE Trans Pattern Anal Mach Intell 33:1548\u20131560","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"11","key":"2011_CR13","doi-asserted-by":"publisher","first-page":"3545","DOI":"10.1007\/s00500-018-3109-x","volume":"22","author":"Y Yi","year":"2018","unstructured":"Yi Y, Qiao S, Zhou W, Zheng C, Liu Q, Wang J (2018) Adaptive multiple graph regularized semi-supervised extreme learning machine. Soft Comput 22(11):3545\u20133562","journal-title":"Soft Comput"},{"key":"2011_CR14","doi-asserted-by":"publisher","first-page":"54479","DOI":"10.1109\/ACCESS.2018.2871884","volume":"6","author":"C Zheng","year":"2018","unstructured":"Zheng C, Zhao R, Liu F, Kong J, Wang J, Bi C, Yi Y (2018) Dimensionality reduction via multiple locality-constrained graph optimizations. IEEE Access 6:54479\u201354494","journal-title":"IEEE Access"},{"key":"2011_CR15","unstructured":"Yu K et al (2009) Nonlinear learning using local coordinate coding. In: Advances in neural information processing systems 2223\u20132231"},{"key":"2011_CR16","doi-asserted-by":"publisher","first-page":"1277","DOI":"10.1016\/j.patcog.2012.11.014","volume":"46","author":"CP Wei","year":"2013","unstructured":"Wei CP, Chao YW, Yeh YR, Wang YCF (2013) Locality-sensitive dictionary learning for sparse representation based classification. Pattern Recogn 46:1277\u20131287","journal-title":"Pattern Recogn"},{"key":"2011_CR17","doi-asserted-by":"crossref","unstructured":"Chao YW et al (2011) Locality-constrained group sparse representation for robust face recognition. In: 18th IEEE international conference on image processing (ICIP). IEEE, pp 761\u2013764","DOI":"10.1109\/ICIP.2011.6116666"},{"key":"2011_CR18","doi-asserted-by":"publisher","first-page":"1327","DOI":"10.1109\/TIP.2010.2090535","volume":"20","author":"M Zheng","year":"2011","unstructured":"Zheng M et al (2011) Graph regularized sparse coding for image representation. IEEE Trans Image Process 20:1327\u20131336","journal-title":"IEEE Trans Image Process"},{"key":"2011_CR19","doi-asserted-by":"publisher","first-page":"1486","DOI":"10.1016\/j.neucom.2015.07.084","volume":"171","author":"H Min","year":"2016","unstructured":"Min H, Liang M, Luo R, Zhu J (2016) Laplacian regularized locality-constrained coding for image classification. Neurocomputing 171:1486\u20131495","journal-title":"Neurocomputing"},{"key":"2011_CR20","doi-asserted-by":"crossref","unstructured":"Yao T et al (2015) Discovering commonness and specificness for human action recognition. In: The 2nd ACM international workshop on human-centered event understanding from multimedia. ACM, pp 7\u201312","DOI":"10.1145\/2815244.2815247"},{"key":"2011_CR21","doi-asserted-by":"crossref","unstructured":"Wang S, Fu Y (2015) Locality-constrained discriminative learning and coding. In: IEEE conference on computer vision and pattern recognition workshops. IEEE, pp 17\u201324","DOI":"10.1109\/CVPRW.2015.7301315"},{"issue":"2","key":"2011_CR22","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1214\/009053604000000067","volume":"32","author":"B Efron","year":"2004","unstructured":"Efron B et al (2004) Least angle regression. Ann Stat 32(2):407\u2013499","journal-title":"Ann Stat"},{"key":"2011_CR23","doi-asserted-by":"publisher","first-page":"118","DOI":"10.1016\/j.ins.2015.07.005","volume":"325","author":"F Dornaika","year":"2015","unstructured":"Dornaika F, Bosaghzadeh A (2015) Adaptive graph construction using data self-representativeness for pattern classification. Inf Sci 325:118\u2013139","journal-title":"Inf Sci"},{"key":"2011_CR24","doi-asserted-by":"publisher","first-page":"1624","DOI":"10.1109\/TKDE.2005.198","volume":"17","author":"D Cai","year":"2005","unstructured":"Cai D, He X, Han J (2005) Document clustering using locality preserving indexing. IEEE Trans Knowl Data Eng 17:1624\u20131637","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"2011_CR25","doi-asserted-by":"publisher","first-page":"2167","DOI":"10.1109\/TNNLS.2014.2306063","volume":"25","author":"K Tang","year":"2014","unstructured":"Tang K, Liu R, Su Z, Zhang J (2014) Structure-constrained low-rank representation. IEEE Trans Neural Netw Learn Syst 25:2167\u20132179","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"2011_CR26","doi-asserted-by":"publisher","first-page":"1672","DOI":"10.1109\/TPAMI.2008.114","volume":"30","author":"N Kwak","year":"2008","unstructured":"Kwak N (2008) Principal component analysis based on L1-norm maximization. IEEE Trans Pattern Anal Mach Intell 30:1672\u20131680","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"2011_CR27","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1016\/j.neucom.2012.08.007","volume":"101","author":"F Shen","year":"2013","unstructured":"Shen F, Tang Z, Xu J (2013) Locality constrained representation based classification with spatial pyramid patches. Neurocomputing 101:104\u2013115","journal-title":"Neurocomputing"},{"issue":"9","key":"2011_CR28","doi-asserted-by":"publisher","first-page":"2069","DOI":"10.1587\/transfun.E100.A.2069","volume":"E100. A","author":"W Zhou","year":"2017","unstructured":"Zhou W et al (2017) Automatic optic disc boundary extraction based on saliency object detection and modified local intensity clustering model in retinal images. IEICE Trans Fundam Electron Commun Comput Sci E100. A(9):2069\u20132072","journal-title":"IEICE Trans Fundam Electron Commun Comput Sci"},{"key":"2011_CR29","doi-asserted-by":"crossref","unstructured":"Abdullah AS et al (2018) A novel method for retinal optic disc detection using bat meta-heuristic algorithm. Med Biol Eng Comput 1\u201310","DOI":"10.1007\/s11517-018-1840-1"},{"issue":"1","key":"2011_CR30","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.media.2014.08.002","volume":"19","author":"G Azzopardi","year":"2015","unstructured":"Azzopardi G, Strisciuglio N, Vento M, Petkov N (2015) Trainable cosfire filters for vessel delineation with application to retinal images. Med Image Anal 19(1):46\u201357","journal-title":"Med Image Anal"},{"key":"2011_CR31","doi-asserted-by":"crossref","unstructured":"Yin F et al (2012) Automated segmentation of optic disc and optic cup in fundus images for glaucoma diagnosis. In: 2012 25th international symposium on computer-based medical systems (CBMS). IEEE, pp 1\u20136","DOI":"10.1109\/CBMS.2012.6266344"},{"key":"2011_CR32","doi-asserted-by":"crossref","unstructured":"Liu J et al (2008) Optic cup and disk extraction from retinal fundus images for determination of cup-to-disc ratio. In: IEEE conference on industrial electronics and applications. IEEE, pp 1828\u20131832","DOI":"10.1109\/ICIEA.2008.4582835"},{"key":"2011_CR33","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1016\/S0925-2312(02)00782-8","volume":"52","author":"PO Hoyer","year":"2003","unstructured":"Hoyer PO (2003) Modeling receptive fields with non-negative sparse coding. Neurocomputing 52:547\u2013552","journal-title":"Neurocomputing"},{"issue":"6","key":"2011_CR34","doi-asserted-by":"publisher","first-page":"1871","DOI":"10.1109\/TSMCB.2012.2234108","volume":"43","author":"P Li","year":"2013","unstructured":"Li P, Bu J, Chen C, He Z, Cai D (2013) Relational multimanifold coclustering. IEEE Trans Cybern 43(6):1871\u20131881","journal-title":"IEEE Trans Cybern"},{"key":"2011_CR35","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.image.2018.03.005","volume":"65","author":"Y Cui","year":"2018","unstructured":"Cui Y et al (2018) New semi-supervised classification using a multi-modal feature joint L21-norm based sparse representation. Signal Process Image Commun 65:94\u2013106","journal-title":"Signal Process Image Commun"},{"key":"2011_CR36","doi-asserted-by":"publisher","first-page":"132","DOI":"10.1016\/j.neucom.2015.04.085","volume":"167","author":"Y Yi","year":"2015","unstructured":"Yi Y, Bi C, Li X, Wang J, Kong J (2015) Semi-supervised local ridge regression for local matching based face recognition. Neurocomputing 167:132\u2013146","journal-title":"Neurocomputing"},{"key":"2011_CR37","doi-asserted-by":"crossref","unstructured":"Platt J (1999) Fast training of support vector machines using sequential minimal optimization. In: Advances in Kernel methods. MIT Press","DOI":"10.7551\/mitpress\/1130.003.0016"},{"key":"2011_CR38","unstructured":"Lin Z, Chen M, Ma Y (2010) The augmented Lagrange multiplier method for exact recovery of corrupted low-rank matrices. arXiv preprint arXiv: 1009. 5055"},{"key":"2011_CR39","unstructured":"Rudin W (1976) Principles of mathematical analysis. 3(4.2):1, McGraw-hill New York"},{"issue":"1","key":"2011_CR40","first-page":"1004","volume":"2","author":"J Sivaswamy","year":"2015","unstructured":"Sivaswamy J et al (2015) A comprehensive retinal image dataset for the assessment of glaucoma from the optic nerve head analysis. JSM Biomed Imaging Data Pap 2(1):1004","journal-title":"JSM Biomed Imaging Data Pap"},{"key":"2011_CR41","doi-asserted-by":"crossref","unstructured":"Fumero F et al (2011) RIM-ONE: an open retinal image database for optic nerve evaluation. In: The 24th international symposium on computer-based medical systems (CBMS). IEEE, pp 1\u20136","DOI":"10.1109\/CBMS.2011.5999143"},{"key":"2011_CR42","doi-asserted-by":"publisher","unstructured":"Santos E, Santos L, Veras R, et al (2018) A semiautomatic superpixel based approach to cup-to-disc ratio measurement. 2018 IEEE symposium on computers and communications (ISCC). https:\/\/doi.org\/10.1109\/ISCC.2018.8538765","DOI":"10.1109\/ISCC.2018.8538765"},{"issue":"1","key":"2011_CR43","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1109\/TITB.2011.2176540","volume":"16","author":"S Dua","year":"2012","unstructured":"Dua S, Acharya UR, Chowriappa P, Sree SV (2012) Wavelet-based energy features for glaucomatous image classification. IEEE Trans Inf Technol Biomed 16(1):80\u201387","journal-title":"IEEE Trans Inf Technol Biomed"},{"key":"2011_CR44","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.compmedimag.2019.02.005","volume":"74","author":"S Yu","year":"2019","unstructured":"Yu S, Xiao D, Frost S, Kanagasingam Y (2019) Robust optic disc and cup segmentation with deep learning for glaucoma detection. Comput Med Imaging Graph 74:61\u201371","journal-title":"Comput Med Imaging Graph"},{"issue":"1","key":"2011_CR45","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/TIT.1967.1053964","volume":"13","author":"T Cover","year":"1967","unstructured":"Cover T, Hart P (1967) Nearest neighbor pattern classification. IEEE Trans Inf Theory 13(1):21\u201327","journal-title":"IEEE Trans Inf Theory"},{"issue":"5500","key":"2011_CR46","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","volume":"290","author":"S Roweis","year":"2000","unstructured":"Roweis S, Saul L (2000) Linear dimensionality reduction by locally linear embedding. Science 290(5500):2323\u20132326","journal-title":"Science"},{"issue":"6583","key":"2011_CR47","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1038\/381607a0","volume":"381","author":"BA Olshausen","year":"1996","unstructured":"Olshausen BA, Field DJ (1996) Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381(6583):607\u2013609","journal-title":"Nature"},{"issue":"9","key":"2011_CR48","doi-asserted-by":"publisher","first-page":"2794","DOI":"10.1016\/j.patcog.2014.03.013","volume":"47","author":"X Peng","year":"2014","unstructured":"Peng X, Zhang L, Yi Z, Tan KK (2014) Learning locality-constrained collaborative representation for robust face recognition. Pattern Recogn 47(9):2794\u20132806","journal-title":"Pattern Recogn"},{"key":"2011_CR49","doi-asserted-by":"publisher","unstructured":"Fu H, Cheng J, Xu Y, et al (2018) Joint optic disc and cup segmentation based on multi-label deep network and polar transformation. IEEE transactions on medical imaging. https:\/\/doi.org\/10.1109\/TMI.2018.2791488","DOI":"10.1109\/TMI.2018.2791488"},{"key":"2011_CR50","doi-asserted-by":"publisher","unstructured":"Ayub J, Ahmad J, Muhammad J, et al (2016) Glaucoma detection through optic disc and cup segmentation using K-mean clustering. 2016 International conference on computing, electronic and electrical engineering (ICE Cube). https:\/\/doi.org\/10.1109\/ICECUBE.2016.7495212","DOI":"10.1109\/ICECUBE.2016.7495212"}],"container-title":["Medical &amp; Biological Engineering &amp; Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-019-02011-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11517-019-02011-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-019-02011-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,18]],"date-time":"2023-09-18T16:21:39Z","timestamp":1695054099000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11517-019-02011-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,27]]},"references-count":50,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["2011"],"URL":"https:\/\/doi.org\/10.1007\/s11517-019-02011-z","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"type":"print","value":"0140-0118"},{"type":"electronic","value":"1741-0444"}],"subject":[],"published":{"date-parts":[[2019,7,27]]},"assertion":[{"value":"8 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 July 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}