{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T15:57:07Z","timestamp":1775577427677,"version":"3.50.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"22","license":[{"start":{"date-parts":[[2018,1,16]],"date-time":"2018-01-16T00:00:00Z","timestamp":1516060800000},"content-version":"tdm","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":["61703301"],"award-info":[{"award-number":["61703301"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61573023"],"award-info":[{"award-number":["61573023"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2018,11]]},"DOI":"10.1007\/s11042-017-5581-1","type":"journal-article","created":{"date-parts":[[2018,1,16]],"date-time":"2018-01-16T08:11:22Z","timestamp":1516090282000},"page":"29669-29686","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":58,"title":["Multi-task neural networks for joint hippocampus segmentation and clinical score regression"],"prefix":"10.1007","volume":"77","author":[{"given":"Liang","family":"Cao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Long","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jifeng","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,1,16]]},"reference":[{"key":"5581_CR1","unstructured":"Abadi M, Barham P, Chen J, Chen Z, Davis A, Dean J, Devin M, Ghemawat S, Irving G, Isard M et al (2016) Tensorflow: A system for large-scale machine learning. In: Proceedings of the 12th USENIX symposium on operating systems design and implementation"},{"key":"5581_CR2","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1016\/j.compmedimag.2015.04.007","volume":"44","author":"OB Ahmed","year":"2015","unstructured":"Ahmed O B, Mizotin M, Benois-Pineau J, Allard M, Catheline G, Amar C B, Initiative A D N et al (2015) Alzheimer\u2019s disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex. Comput Med Imaging Graph 44:13\u201325","journal-title":"Comput Med Imaging Graph"},{"issue":"1","key":"5581_CR3","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","volume":"38","author":"J Ashburner","year":"2007","unstructured":"Ashburner J (2007) A fast diffeomorphic image registration algorithm. NeuroImage 38(1):95\u2013113","journal-title":"NeuroImage"},{"issue":"11","key":"5581_CR4","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1016\/j.neurobiolaging.2006.07.008","volume":"28","author":"J Barnes","year":"2007","unstructured":"Barnes J, Boyes R, Lewis E, Schott J, Frost C, Scahill R, Fox N (2007) Automatic calculation of hippocampal atrophy rates using a hippocampal template and the boundary shift integral. Neurobiol Aging 28(11):1657\u20131663","journal-title":"Neurobiol Aging"},{"key":"5581_CR5","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511804441","volume-title":"Convex optimization","author":"S Boyd","year":"2004","unstructured":"Boyd S, Vandenberghe L (2004) Convex optimization. Cambridge University Press, Cambridge"},{"key":"5581_CR6","doi-asserted-by":"crossref","unstructured":"Cao X, Gao Y, Yang J, Wu G, Shen D (2016) Learning-based multimodal image registration for prostate cancer radiation therapy. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, pp 1\u20139","DOI":"10.1007\/978-3-319-46726-9_1"},{"key":"5581_CR7","doi-asserted-by":"crossref","unstructured":"Cao X, Yang J, Gao Y, Guo Y, Wu G, Shen D (2017) Dual-core steered non-rigid registration for multi-modal images via bi-directional image synthesis. Medical Image Analysis","DOI":"10.1016\/j.media.2017.05.004"},{"issue":"4","key":"5581_CR8","doi-asserted-by":"publisher","first-page":"979","DOI":"10.1016\/j.neuroimage.2005.05.005","volume":"27","author":"OT Carmichael","year":"2005","unstructured":"Carmichael O T, Aizenstein H A, Davis S W, Becker J T, Thompson P M, Meltzer C C, Liu Y (2005) Atlas-based hippocampus segmentation in Alzheimer\u2019s disease and mild cognitive impairment. NeuroImage 27(4):979\u2013990","journal-title":"NeuroImage"},{"issue":"3","key":"5581_CR9","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1145\/1961189.1961199","volume":"2","author":"CC Chang","year":"2011","unstructured":"Chang C C, Lin C J (2011) Libsvm: A library for support vector machines. ACM Trans Intell Syst Technol 2(3):27","journal-title":"ACM Trans Intell Syst Technol"},{"issue":"2","key":"5581_CR10","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1016\/j.neuroimage.2011.05.083","volume":"58","author":"A Chincarini","year":"2011","unstructured":"Chincarini A, Bosco P, Calvini P, Gemme G, Esposito M, Olivieri C, Rei L, Squarcia S, Rodriguez G, Bellotti R et al (2011) Local MRI analysis approach in the diagnosis of early and prodromal Alzheimer\u2019s disease. NeuroImage 58 (2):469\u2013480","journal-title":"NeuroImage"},{"issue":"1","key":"5581_CR11","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.neuroimage.2005.07.035","volume":"29","author":"KA Clark","year":"2006","unstructured":"Clark K A, Woods R P, Rottenberg D A, Toga A W, Mazziotta J C (2006) Impact of acquisition protocols and processing streams on tissue segmentation of T1 weighted MR images. NeuroImage 29(1):185\u2013202","journal-title":"NeuroImage"},{"issue":"2","key":"5581_CR12","doi-asserted-by":"publisher","first-page":"940","DOI":"10.1016\/j.neuroimage.2010.09.018","volume":"54","author":"P Coup\u00e9","year":"2011","unstructured":"Coup\u00e9 P, Manj\u00f3n J V, Fonov V, Pruessner J, Robles M, Collins D L (2011) Patch-based segmentation using expert priors: Application to hippocampus and ventricle segmentation. NeuroImage 54(2):940\u2013954","journal-title":"NeuroImage"},{"issue":"4","key":"5581_CR13","doi-asserted-by":"publisher","first-page":"3736","DOI":"10.1016\/j.neuroimage.2011.10.080","volume":"59","author":"P Coup\u00e9","year":"2012","unstructured":"Coup\u00e9 P, Eskildsen S F, Manj\u00f3n J V, Fonov V S, Collins D L (2012) Simultaneous segmentation and grading of anatomical structures for patient\u2019s classification: Application to Alzheimer\u2019s disease. NeuroImage 59(4):3736\u20133747","journal-title":"NeuroImage"},{"issue":"5","key":"5581_CR14","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.1093\/brain\/124.5.1020","volume":"124","author":"A Dagher","year":"2001","unstructured":"Dagher A, Owen A M, Boecker H, Brooks D J (2001) The role of the striatum and hippocampus in planning: A PET activation study in Parkinson\u2019s disease. Brain 124(5):1020\u20131032","journal-title":"Brain"},{"issue":"2","key":"5581_CR15","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s12021-014-9243-4","volume":"13","author":"V Dill","year":"2015","unstructured":"Dill V, Franco A R, Pinho M S (2015) Automated methods for hippocampus segmentation: The evolution and a review of the state of the art. Neuroinformatics 13 (2):133","journal-title":"Neuroinformatics"},{"issue":"3","key":"5581_CR16","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/0022-3956(75)90026-6","volume":"12","author":"MF Folstein","year":"1975","unstructured":"Folstein M F, Folstein S E, McHugh P R (1975) \u201cmini-mental state\u201d. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12(3):189\u2013198","journal-title":"J Psychiatr Res"},{"issue":"6","key":"5581_CR17","doi-asserted-by":"publisher","first-page":"2674","DOI":"10.1002\/hbm.22359","volume":"35","author":"Y Hao","year":"2014","unstructured":"Hao Y, Wang T, Zhang X, Duan Y, Yu C, Jiang T, Fan Y (2014) Local label learning (LLL) for subcortical structure segmentation: Application to hippocampus segmentation. Hum Brain Mapp 35 (6):2674\u20132697","journal-title":"Hum Brain Mapp"},{"issue":"1","key":"5581_CR18","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1016\/j.neuroimage.2006.05.061","volume":"33","author":"RA Heckemann","year":"2006","unstructured":"Heckemann R A, Hajnal J V, Aljabar P, Rueckert D, Hammers A (2006) Automatic anatomical brain MRI segmentation combining label propagation and decision fusion. NeuroImage 33(1):115\u2013126","journal-title":"NeuroImage"},{"key":"5581_CR19","doi-asserted-by":"publisher","first-page":"1168","DOI":"10.1126\/science.6474172","volume":"225","author":"BT Hyman","year":"1984","unstructured":"Hyman B T, Van Hoesen G W, Damasio A R, Barnes C L (1984) Alzheimer\u2019s disease: Cell-specific pathology isolates the hippocampal formation. Science 225:1168\u20131171","journal-title":"Science"},{"issue":"1","key":"5581_CR20","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.media.2015.06.012","volume":"24","author":"JE Iglesias","year":"2015","unstructured":"Iglesias J E, Sabuncu M R (2015) Multi-atlas segmentation of biomedical images: A survey. Med Image Anal 24(1):205\u2013219","journal-title":"Med Image Anal"},{"issue":"1","key":"5581_CR21","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1212\/WNL.42.1.183","volume":"42","author":"CR Jack","year":"1992","unstructured":"Jack C R, Petersen R C, O\u2019Brien P C, Tangalos E G (1992) MR-based hippocampal volumetry in the diagnosis of Alzheimer\u2019s disease. Neurology 42(1):183\u2013183","journal-title":"Neurology"},{"issue":"4","key":"5581_CR22","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1002\/jmri.21049","volume":"27","author":"CR Jack","year":"2008","unstructured":"Jack C R, Bernstein M A, Fox N C, Thompson P, Alexander G, Harvey D, Borowski B, Britson P J, L Whitwell J, Ward C (2008) The Alzheimer\u2019s disease neuroimaging initiative (ADNI): MRI methods. J Magn Reson Imaging 27(4):685\u2013691","journal-title":"J Magn Reson Imaging"},{"issue":"1","key":"5581_CR23","doi-asserted-by":"publisher","first-page":"343","DOI":"10.1073\/pnas.2634794100","volume":"101","author":"K Jin","year":"2004","unstructured":"Jin K, Peel A L, Mao X O, Xie L, Cottrell B A, Henshall D C, Greenberg D A (2004) Increased hippocampal neurogenesis in Alzheimer\u2019s disease. Proc Natl Acad Sci 101(1):343\u2013347","journal-title":"Proc Natl Acad Sci"},{"issue":"7","key":"5581_CR24","doi-asserted-by":"publisher","first-page":"1190","DOI":"10.1016\/j.mri.2013.04.008","volume":"31","author":"K Kwak","year":"2013","unstructured":"Kwak K, Yoon U, Lee D K, Kim G H, Seo S W, Na D L, Shim H J, Lee J M (2013) Fully-automated approach to hippocampus segmentation using a graph-cuts algorithm combined with atlas-based segmentation and morphological opening. Magn Reson Imaging 31(7):1190\u20131196","journal-title":"Magn Reson Imaging"},{"issue":"7","key":"5581_CR25","doi-asserted-by":"publisher","first-page":"2318","DOI":"10.1016\/j.patcog.2015.01.019","volume":"48","author":"C Lian","year":"2015","unstructured":"Lian C, Ruan S, Denoeux T (2015) An evidential classifier based on feature selection and two-step classification strategy. Pattern Recogn 48(7):2318\u20132327","journal-title":"Pattern Recogn"},{"key":"5581_CR26","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1016\/j.media.2016.05.007","volume":"32","author":"C Lian","year":"2016","unstructured":"Lian C, Ruan S, Den\u0153ux T, Jardin F, Vera P (2016) Selecting radiomic features from FDG-PET images for cancer treatment outcome prediction. Med Image Anal 32:257\u2013268","journal-title":"Med Image Anal"},{"issue":"8","key":"5581_CR27","doi-asserted-by":"publisher","first-page":"1462","DOI":"10.1109\/TMI.2013.2258030","volume":"32","author":"C Lindner","year":"2013","unstructured":"Lindner C, Thiagarajah S, Wilkinson J, Consortium T, Wallis G, Cootes T (2013) Fully automatic segmentation of the proximal femur using random forest regression voting. IEEE Trans Med Imaging 32(8):1462\u20131472","journal-title":"IEEE Trans Med Imaging"},{"issue":"5","key":"5581_CR28","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1002\/hbm.22741","volume":"36","author":"M Liu","year":"2015","unstructured":"Liu M, Zhang D, Shen D (2015) View-centralized multi-atlas classification for Alzheimer\u2019s disease diagnosis. Hum Brain Mapp 36(5):1847\u20131865","journal-title":"Hum Brain Mapp"},{"issue":"11","key":"5581_CR29","doi-asserted-by":"publisher","first-page":"2335","DOI":"10.1109\/TPAMI.2015.2430325","volume":"38","author":"M Liu","year":"2016","unstructured":"Liu M, Zhang D, Chen S, Xue H (2016) Joint binary classifier learning for ECOC-based multi-class classification. IEEE Trans Pattern Anal Mach Intell 38 (11):2335\u20132341","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"6","key":"5581_CR30","doi-asserted-by":"publisher","first-page":"1463","DOI":"10.1109\/TMI.2016.2515021","volume":"35","author":"M Liu","year":"2016","unstructured":"Liu M, Zhang D, Shen D (2016) Relationship induced multi-template learning for diagnosis of Alzheimer\u2019s disease and mild cognitive impairment. IEEE Trans Med Imaging 35(6):1463\u20131474","journal-title":"IEEE Trans Med Imaging"},{"key":"5581_CR31","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.media.2016.11.002","volume":"36","author":"M Liu","year":"2017","unstructured":"Liu M, Zhang J, Yap P T, Shen D (2017) View-aligned hypergraph learning for alzheimer\u2019s disease diagnosis with incomplete multi-modality data. Med Image Anal 36:123\u2013134","journal-title":"Med Image Anal"},{"key":"5581_CR32","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.media.2017.10.005","volume":"43","author":"M Liu","year":"2018","unstructured":"Liu M, Zhang J, Adeli E, Shen D (2018) Landmark-based deep multi-instance learning for brain disease diagnosis. Med Image Anal 43:157\u2013168","journal-title":"Med Image Anal"},{"issue":"8","key":"5581_CR33","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1002\/hipo.22417","volume":"25","author":"K Moodley","year":"2015","unstructured":"Moodley K, Minati L, Contarino V, Prioni S, Wood R, Cooper R, D\u2019incerti L, Tagliavini F, Chan D (2015) Diagnostic differentiation of mild cognitive impairment due to Alzheimer\u2019s disease using a hippocampus-dependent test of spatial memory. Hippocampus 25(8):939\u2013951","journal-title":"Hippocampus"},{"issue":"9","key":"5581_CR34","doi-asserted-by":"publisher","first-page":"1201","DOI":"10.1109\/TMI.2007.901433","volume":"26","author":"KM Pohl","year":"2007","unstructured":"Pohl K M, Bouix S, Nakamura M, Rohlfing T, McCarley R W, Kikinis R, Grimson W E L, Shenton M E, Wells W M (2007) A hierarchical algorithm for MR brain image parcellation. IEEE Trans Med Imaging 26(9):1201\u20131212","journal-title":"IEEE Trans Med Imaging"},{"key":"5581_CR35","doi-asserted-by":"crossref","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation. arXiv: 150504597","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"1","key":"5581_CR36","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1109\/42.668698","volume":"17","author":"JG Sled","year":"1998","unstructured":"Sled J G, Zijdenbos A P, Evans A C (1998) A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 17(1):87\u201397","journal-title":"IEEE Trans Med Imaging"},{"issue":"3","key":"5581_CR37","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1002\/(SICI)1098-1063(1998)8:3<198::AID-HIPO2>3.0.CO;2-G","volume":"8","author":"E Tulving","year":"1998","unstructured":"Tulving E, Markowitsch H J (1998) Episodic and declarative memory: Role of the hippocampus. Hippocampus 8(3):198\u2013204","journal-title":"Hippocampus"},{"key":"5581_CR38","doi-asserted-by":"crossref","unstructured":"Zandifar A, Fonov V, Coup\u00e9 P, Pruessner J, Collins DL, Initiative ADN et al (2017) A comparison of accurate automatic hippocampal segmentation methods. NeuroImage","DOI":"10.1016\/j.neuroimage.2017.04.018"},{"key":"5581_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/JTEHM.2014.2297953","volume":"2","author":"D Zarpalas","year":"2014","unstructured":"Zarpalas D, Gkontra P, Daras P, Maglaveras N (2014) Accurate and fully automatic hippocampus segmentation using subject-specific 3D optimal local maps into a hybrid active contour model. IEEE J Trans Eng Health Med 2:1\u201316","journal-title":"IEEE J Trans Eng Health Med"},{"issue":"1","key":"5581_CR40","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1109\/TIP.2012.2214045","volume":"22","author":"J Zhang","year":"2013","unstructured":"Zhang J, Liang J, Zhao H (2013) Local energy pattern for texture classification using self-adaptive quantization thresholds. IEEE Trans Image Process 22(1):31\u201342","journal-title":"IEEE Trans Image Process"},{"issue":"9","key":"5581_CR41","doi-asserted-by":"publisher","first-page":"1820","DOI":"10.1109\/TBME.2015.2503421","volume":"63","author":"J Zhang","year":"2016","unstructured":"Zhang J, Gao Y, Wang L, Tang Z, Xia J J, Shen D (2016) Automatic craniomaxillofacial landmark digitization via segmentation-guided partially-joint regression forest model and multiscale statistical features. IEEE Trans Biomed Eng 63(9):1820\u20131829","journal-title":"IEEE Trans Biomed Eng"},{"key":"5581_CR42","doi-asserted-by":"crossref","unstructured":"Zhang J, Gao Y, Park SH, Zong X, Lin W, Shen D (2017) Structured learning for 3D perivascular spaces segmentation using vascular features. IEEE Transactions on Biomedical Engineering","DOI":"10.1109\/TBME.2016.2638918"},{"key":"5581_CR43","doi-asserted-by":"crossref","unstructured":"Zhang J, Liu M, An L, Gao Y, Shen D (2017) Alzheimer\u2019s disease diagnosis using landmark-based features from longitudinal structural MR images. IEEE Journal of Biomedical and Health Informatics","DOI":"10.1109\/JBHI.2017.2704614"},{"issue":"10","key":"5581_CR44","doi-asserted-by":"publisher","first-page":"4753","DOI":"10.1109\/TIP.2017.2721106","volume":"26","author":"J Zhang","year":"2017","unstructured":"Zhang J, Liu M, Shen D (2017) Detecting anatomical landmarks from limited medical imaging data using two-stage task-oriented deep neural networks. IEEE Trans Image Process 26(10):4753\u20134764","journal-title":"IEEE Trans Image Process"},{"key":"5581_CR45","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.neuroimage.2014.05.078","volume":"100","author":"X Zhu","year":"2014","unstructured":"Zhu X, Suk H I, Shen D (2014) A novel matrix-similarity based loss function for joint regression and classification in AD diagnosis. NeuroImage 100:91\u2013105","journal-title":"NeuroImage"},{"key":"5581_CR46","unstructured":"Zhu X, Suk H I, Wang L, Lee SW, Shen D (2015) A novel relational regularization feature selection method for joint regression and classification in AD diagnosis. Medical Image analysis"},{"key":"5581_CR47","doi-asserted-by":"crossref","unstructured":"Zhu Y, Zhu X, Kim M, Shen D, Wu G (2016) Early diagnosis of Alzheimer\u2019s disease by joint feature selection and classification on temporally structured support vector machine. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, pp 264\u2013272","DOI":"10.1007\/978-3-319-46720-7_31"},{"key":"5581_CR48","doi-asserted-by":"crossref","unstructured":"Zhu Y, Zhu X, Zhang H, Gao W, Shen D, Wu G (2016) Reveal consistent spatial-temporal patterns from dynamic functional connectivity for autism spectrum disorder identification. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, Springer, pp 106\u2013114","DOI":"10.1007\/978-3-319-46720-7_13"},{"key":"5581_CR49","doi-asserted-by":"crossref","unstructured":"Zhu Y, Zhu X, Kim M, Kaufer D, Wu G (2017) A novel dynamic hyper-graph inference framework for computer assisted diagnosis of neuro-diseases. In: International Conference on Information Processing in Medical Imaging, Springer, pp 158\u2013169","DOI":"10.1007\/978-3-319-59050-9_13"},{"issue":"2","key":"5581_CR50","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/S1076-6332(03)00671-8","volume":"11","author":"KH Zou","year":"2004","unstructured":"Zou K H, Warfield S K, Bharatha A, Tempany C M, Kaus M R, Haker S J, Wells W M, Jolesz F A, Kikinis R (2004) Statistical validation of image segmentation quality based on a spatial overlap index 1: Scientific reports. Acad Radiol 11(2):178\u2013189","journal-title":"Acad Radiol"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-017-5581-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-017-5581-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-017-5581-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T14:28:49Z","timestamp":1719757729000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-017-5581-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1,16]]},"references-count":50,"journal-issue":{"issue":"22","published-print":{"date-parts":[[2018,11]]}},"alternative-id":["5581"],"URL":"https:\/\/doi.org\/10.1007\/s11042-017-5581-1","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,1,16]]},"assertion":[{"value":"9 July 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 November 2017","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 December 2017","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 January 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}