{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T20:46:38Z","timestamp":1761597998243,"version":"3.37.3"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2018,10,17]],"date-time":"2018-10-17T00:00:00Z","timestamp":1539734400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001807","name":"FAPESP","doi-asserted-by":"crossref","award":["14\/12236-1"],"award-info":[{"award-number":["14\/12236-1"]}],"id":[{"id":"10.13039\/501100001807","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100003593","name":"CNPq","doi-asserted-by":"crossref","award":["302970\/2014-2"],"award-info":[{"award-number":["302970\/2014-2"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neuroinform"],"published-print":{"date-parts":[[2019,4]]},"DOI":"10.1007\/s12021-018-9390-0","type":"journal-article","created":{"date-parts":[[2018,10,17]],"date-time":"2018-10-17T01:59:08Z","timestamp":1539741548000},"page":"307-321","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease"],"prefix":"10.1007","volume":"17","author":[{"name":"Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6427-6143","authenticated-orcid":false,"given":"Alexandre Yukio","family":"Yamashita","sequence":"first","affiliation":[]},{"given":"Alexandre Xavier","family":"Falc\u00e3o","sequence":"additional","affiliation":[]},{"given":"Neucimar Jer\u00f4nimo","family":"Leite","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,10,17]]},"reference":[{"key":"9390_CR1","unstructured":"Alzheimer\u2019s Association. (2017). Alzheimer\u2019s disease and dementia. \n                    http:\/\/www.alz.org\/\n                    \n                  . [Online; accessed 20 Dec 2017]."},{"key":"9390_CR2","unstructured":"Ambastha, A.K. (2015). Neuroanatomical characterisation of Alzheimer\u2019s disease using deep learning. National University of Singapore."},{"key":"9390_CR3","unstructured":"Association, A.E.R., Association, A.P., on Measurement in Education, N.C., on Standards for Educational, J.C., (US), P.T. (1999). Standards for educational and psychological testing. American Educational Research Association."},{"issue":"1","key":"9390_CR4","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","volume":"12","author":"BB Avants","year":"2008","unstructured":"Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Medical Image Analysis, 12(1), 26\u201341.","journal-title":"Medical Image Analysis"},{"issue":"1","key":"9390_CR5","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5\u201332.","journal-title":"Machine Learning"},{"issue":"4","key":"9390_CR6","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"},{"key":"9390_CR7","doi-asserted-by":"publisher","first-page":"22","DOI":"10.3389\/fninf.2011.00022","volume":"5","author":"R Casanova","year":"2011","unstructured":"Casanova, R., Whitlow, C.T., Wagner, B., Williamson, J., Shumaker, S.A., Maldjian, J.A., Espeland, M.A. (2011). High dimensional classification of structural MRI Alzheimer\u2019s disease data based on large scale regularization. Frontiers in Neuroinformatics, 5, 22.","journal-title":"Frontiers in Neuroinformatics"},{"issue":"4","key":"9390_CR8","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1109\/TRO.2004.829463","volume":"20","author":"F Chaumette","year":"2004","unstructured":"Chaumette, F. (2004). Image moments: a general and useful set of features for visual servoing. IEEE Transactions on Robotics, 20(4), 713\u2013723.","journal-title":"IEEE Transactions on Robotics"},{"key":"9390_CR9","doi-asserted-by":"crossref","unstructured":"Chen, Y.W., & Lin, C.J. (2006). Combining SVMs with various feature selection strategies. In Feature extraction (pp. 315\u2013324). Springer.","DOI":"10.1007\/978-3-540-35488-8_13"},{"issue":"2","key":"9390_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":"7","key":"9390_CR11","doi-asserted-by":"publisher","first-page":"e6353","DOI":"10.1371\/journal.pone.0006353","volume":"4","author":"SG Costafreda","year":"2009","unstructured":"Costafreda, S.G., Chu, C., Ashburner, J., Fu, C.H. (2009). Prognostic and diagnostic potential of the structural neuroanatomy of depression. PloS one, 4(7), e6353.","journal-title":"PloS one"},{"issue":"1","key":"9390_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/1471-244X-11-18","volume":"11","author":"SG Costafreda","year":"2011","unstructured":"Costafreda, S.G., Fu, C.H., Picchioni, M., Toulopoulou, T., McDonald, C., Kravariti, E., Walshe, M., Prata, D., Murray, R.M., McGuire, P.K. (2011). Pattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorder. BMC Psychiatry, 11(1), 1.","journal-title":"BMC Psychiatry"},{"issue":"4","key":"9390_CR13","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1016\/j.neuroimage.2004.12.034","volume":"25","author":"SB Eickhoff","year":"2005","unstructured":"Eickhoff, S.B., Stephan, K.E., Mohlberg, H., Grefkes, C., Fink, G.R., Amunts, K., Zilles, K. (2005). A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data. NeuroImage, 25(4), 1325\u20131335.","journal-title":"NeuroImage"},{"issue":"3","key":"9390_CR14","doi-asserted-by":"publisher","first-page":"625","DOI":"10.19026\/rjaset.7.299","volume":"7","author":"NOF Elssied","year":"2014","unstructured":"Elssied, N.O.F., Ibrahim, O., Osman, A.H. (2014). A novel feature selection based on one-way ANOVA f-test for e-mail spam classification. Research Journal of Applied Sciences Engineering and Technology, 7(3), 625\u2013638.","journal-title":"Research Journal of Applied Sciences Engineering and Technology"},{"issue":"1","key":"9390_CR15","doi-asserted-by":"publisher","first-page":"313","DOI":"10.1016\/j.neuroimage.2010.07.033","volume":"54","author":"V Fonov","year":"2011","unstructured":"Fonov, V., Evans, A.C., Botteron, K., Almli, C.R., McKinstry, R.C., Collins, D.L. (2011). Brain development cooperative group, others: unbiased average age-appropriate atlases for pediatric studies. NeuroImage, 54(1), 313\u2013327.","journal-title":"NeuroImage"},{"key":"9390_CR16","unstructured":"French, A., Macedo, M., Poulsen, J., Waterson, T., Yu, A. (2017). Multivariate analysis of variance (MANOVA). \n                    http:\/\/userwww.sfsu.edu\/efc\/classes\/biol710\/manova\/MANOVAnewest.pdf\n                    \n                  . [Online; accessed 20 Dec 2017]."},{"key":"9390_CR17","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.bspc.2016.01.009","volume":"27","author":"I Garali","year":"2016","unstructured":"Garali, I., Adel, M., Bourennane, S., Guedj, E. (2016). Brain region ranking for 18FDG-PET computer-aided diagnosis of Alzheimer\u2019s disease. Biomedical Signal Processing and Control, 27, 15\u201323.","journal-title":"Biomedical Signal Processing and Control"},{"key":"9390_CR18","doi-asserted-by":"crossref","unstructured":"Golugula, A., Lee, G., Madabhushi, A. (2011). Evaluating feature selection strategies for high dimensional, small sample size datasets. In 2011 Annual International conference of the IEEE engineering in medicine and biology society (pp. 949\u2013952). IEEE.","DOI":"10.1109\/IEMBS.2011.6090214"},{"key":"9390_CR19","unstructured":"Gr\u00fcnauer, A., & Vincze, M. (2015). Using dimension reduction to improve the classification of high-dimensional data. arXiv:\n                    1505.06907\n                    \n                  ."},{"key":"9390_CR20","unstructured":"Gupta, A., Ayhan, M., Maida, A. (2013). Natural image bases to represent neuroimaging data. In ICML (Vol. 3, pp. 987\u2013994)."},{"key":"9390_CR21","unstructured":"Halldestam, M. (2016). ANOVA-the effect of outliers."},{"issue":"1","key":"9390_CR22","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1148\/radiology.143.1.7063747","volume":"143","author":"JA Hanley","year":"1982","unstructured":"Hanley, J.A., & McNeil, B.J. (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1), 29\u201336.","journal-title":"Radiology"},{"key":"9390_CR23","unstructured":"Heijmans, H.J., & Roerdink, J. (1998). Mathematical morphology and its applications to image and signal processing (Vol. 12). Springer Science & Business Media."},{"issue":"4","key":"9390_CR24","doi-asserted-by":"publisher","first-page":"903","DOI":"10.1016\/j.ins.2010.10.027","volume":"181","author":"I Ill\u00e1n","year":"2011","unstructured":"Ill\u00e1n, I., G\u00f3rriz, J., Ram\u00edrez, J., Salas-Gonzalez, D., L\u00f3pez, M., Segovia, F., Chaves, R., G\u00f3mez-Rio, M., Puntonet, C.G., ADNI, et al. (2011). 18 F-FDG PET imaging analysis for computer aided Alzheimer\u2019s diagnosis. Information Sciences, 181(4), 903\u2013916.","journal-title":"Information Sciences"},{"issue":"4","key":"9390_CR25","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., et al. (2008). The Alzheimer\u2019s disease neuroimaging initiative (ADNI): MRI methods. Journal of Magnetic Resonance Imaging, 27(4), 685\u2013691.","journal-title":"Journal of Magnetic Resonance Imaging"},{"key":"9390_CR26","unstructured":"Jenkinson, M., Pechaud, M., Smith, S. (2005). BET2: MR-based estimation of brain, skull and scalp surfaces. In: Eleventh annual meeting of the organization for human brain mapping (Vol. 17, p. 167)."},{"key":"9390_CR27","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/j.neucom.2014.09.072","volume":"151","author":"L Khedher","year":"2015","unstructured":"Khedher, L., Ram\u00edrez, J., G\u00f3rriz, J.M., Brahim, A., Segovia, F., ADNI, et al. (2015). Early diagnosis of Alzheimer\u2019s disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images. Neurocomputing, 151, 139\u2013150.","journal-title":"Neurocomputing"},{"issue":"3","key":"9390_CR28","doi-asserted-by":"publisher","first-page":"786","DOI":"10.1016\/j.neuroimage.2008.12.037","volume":"46","author":"A Klein","year":"2009","unstructured":"Klein, A., Andersson, J., Ardekani, B.A., Ashburner, J., Avants, B., Chiang, M.C., Christensen, G.E., Collins, D.L., Gee, J., Hellier, P., et al. (2009). Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage, 46(3), 786\u2013802.","journal-title":"NeuroImage"},{"issue":"11","key":"9390_CR29","doi-asserted-by":"publisher","first-page":"2969","DOI":"10.1093\/brain\/awn239","volume":"131","author":"S Kl\u00f6ppel","year":"2008","unstructured":"Kl\u00f6ppel, S., Stonnington, C.M., Barnes, J., Chen, F., Chu, C., Good, C.D., Mader, I., Mitchell, L.A., Patel, A.C., Roberts, C.C., et al. (2008). Accuracy of dementia diagnosis - a direct comparison between radiologists and a computerized method. Brain: A Journal of Neurology, 131(11), 2969\u20132974.","journal-title":"Brain: A Journal of Neurology"},{"key":"9390_CR30","doi-asserted-by":"crossref","unstructured":"Kramer, O. (2016). Scikit-learn. In Machine learning for evolution strategies (pp. 45\u201353). Springer.","DOI":"10.1007\/978-3-319-33383-0_5"},{"key":"9390_CR31","unstructured":"Landini, L., Positano, V., Santarelli, M. (2005). Advanced image processing in magnetic resonance imaging. CRC Press."},{"key":"9390_CR32","doi-asserted-by":"crossref","unstructured":"Landis, J.R., & Koch, G.G. (1977). The measurement of observer agreement for categorical data. Biometrics, 159\u2013174.","DOI":"10.2307\/2529310"},{"issue":"3","key":"9390_CR33","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1007\/s12021-013-9218-x","volume":"12","author":"M Liu","year":"2014","unstructured":"Liu, M., Zhang, D., Shen, D., ADNI, et al. (2014). Identifying informative imaging biomarkers via tree structured sparse learning for AD diagnosis. Neuroinformatics, 12(3), 381\u2013394.","journal-title":"Neuroinformatics"},{"issue":"4","key":"9390_CR34","doi-asserted-by":"publisher","first-page":"1132","DOI":"10.1109\/TBME.2014.2372011","volume":"62","author":"S Liu","year":"2015","unstructured":"Liu, S., Liu, S., Cai, W., Che, H., Pujol, S., Kikinis, R., Feng, D., Fulham, M.J., et al. (2015). Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer\u2019s disease. IEEE Transactions on Biomedical Engineering, 62(4), 1132\u20131140.","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"9390_CR35","unstructured":"Payan, A., & Montana, G. (2015). Predicting Alzheimer\u2019s disease: a neuroimaging study with 3d convolutional neural networks. arXiv:\n                    1502.02506\n                    \n                  ."},{"key":"9390_CR36","doi-asserted-by":"crossref","unstructured":"Rao, A., Lee, Y., Gass, A., Monsch, A. (2011). Classification of Alzheimer\u2019s disease from structural MRI using sparse logistic regression with optional spatial regularization. In 2011 Annual International conference of the IEEE engineering in medicine and biology society, EMBC (pp. 4499\u20134502). IEEE.","DOI":"10.1109\/IEMBS.2011.6091115"},{"key":"9390_CR37","doi-asserted-by":"crossref","unstructured":"Russ, J.C. (2016). The image processing handbook. CRC Press.","DOI":"10.1201\/b10720"},{"issue":"1","key":"9390_CR38","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1016\/j.neucom.2011.03.050","volume":"75","author":"F Segovia","year":"2012","unstructured":"Segovia, F., G\u00f3rriz, J., Ram\u00edrez, J., Salas-Gonzalez, D., \u00c1lvarez, I., L\u00f3pez, M., Chaves, R., ADNI, et al. (2012). A comparative study of feature extraction methods for the diagnosis of Alzheimer\u2019s disease using the ADNI database. Neurocomputing, 75(1), 64\u201371.","journal-title":"Neurocomputing"},{"key":"9390_CR39","doi-asserted-by":"crossref","unstructured":"Segovia, F., Ram\u00edrez, J., G\u00f3rriz, J.M., Chaves, R., Salas-Gonzalez, D., L\u00f3pez, M., \u00c1lvarez, I., Padilla, P., Puntonet, C.G. (2010). Partial least squares for feature extraction of SPECT images. In International Conference on hybrid artificial intelligence systems (pp. 476\u2013483). Springer.","DOI":"10.1007\/978-3-642-13769-3_58"},{"key":"9390_CR40","unstructured":"Sensi, F., Rei, L., Gemme, G., Bosco, P., Chincarini, A. (2014). Global disease index, a novel tool for MTL atrophy assessment. In MICCAI workshop challenge on computer-aided diagnosis of dementia based on structural MRI data (pp. 92\u2013100)."},{"key":"9390_CR41","doi-asserted-by":"crossref","unstructured":"Somasundaram, K., & Genish, T. (2014). The extraction of hippocampus from MRI of human brain using morphological and image binarization techniques. In 2014 International Conference on electronics and communication systems (ICECS) (pp. 1\u20135). IEEE.","DOI":"10.1109\/ECS.2014.6892666"},{"key":"9390_CR42","unstructured":"Walter, B., Blecker, C., Kirsch, P., Sammer, G., Schienle, A., Stark, R., Vaitl, D. (2003). MARINA: an easy to use tool for the creation of MAsks for Region of INterest analyses. In 9th International conference on functional mapping of the human brain (Vol. 19)."},{"key":"9390_CR43","doi-asserted-by":"crossref","unstructured":"Wenlu, Y., Fangyu, H., Xinyun, C., Xudong, H. (2011). ICA-based automatic classification of PET images from ADNI database. In International Conference on neural information processing (pp. 265\u2013272). Springer.","DOI":"10.1007\/978-3-642-24955-6_32"},{"key":"9390_CR44","unstructured":"World Health Organization. (2017). Dementia fact sheet. \n                    http:\/\/www.who.int\/mediacentre\/factsheets\/fs362\/en\/\n                    \n                  . [Online; accessed 20 Dec 2017]."},{"issue":"4","key":"9390_CR45","doi-asserted-by":"publisher","first-page":"775","DOI":"10.3233\/JAD-2011-101371","volume":"24","author":"W Yang","year":"2011","unstructured":"Yang, W., Lui, R.L., Gao, J.H., Chan, T.F., Yau, S.T., Sperling, R.A., Huang, X. (2011). Independent component analysis-based classification of Alzheimer\u2019s disease MRI data. Journal of Alzheimer\u2019s Disease, 24(4), 775\u2013783.","journal-title":"Journal of Alzheimer\u2019s Disease"}],"container-title":["Neuroinformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12021-018-9390-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s12021-018-9390-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s12021-018-9390-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,16]],"date-time":"2019-10-16T19:05:45Z","timestamp":1571252745000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s12021-018-9390-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,10,17]]},"references-count":45,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,4]]}},"alternative-id":["9390"],"URL":"https:\/\/doi.org\/10.1007\/s12021-018-9390-0","relation":{},"ISSN":["1539-2791","1559-0089"],"issn-type":[{"type":"print","value":"1539-2791"},{"type":"electronic","value":"1559-0089"}],"subject":[],"published":{"date-parts":[[2018,10,17]]},"assertion":[{"value":"17 October 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}