{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T09:40:04Z","timestamp":1744882804132,"version":"3.40.4"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031869198","type":"print"},{"value":"9783031869204","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-86920-4_15","type":"book-chapter","created":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T08:58:06Z","timestamp":1744880286000},"page":"164-174","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Introducing QuantConn: Overcoming Challenging Diffusion Acquisitions with\u00a0Harmonization"],"prefix":"10.1007","author":[{"given":"Nancy","family":"Newlin","sequence":"first","affiliation":[]},{"given":"Kurt","family":"Schilling","sequence":"additional","affiliation":[]},{"given":"Serge","family":"Koudoro","sequence":"additional","affiliation":[]},{"given":"Bramsh Qamar","family":"Chandio","sequence":"additional","affiliation":[]},{"given":"Praitayini","family":"Kanakaraj","sequence":"additional","affiliation":[]},{"given":"Daniel","family":"Moyer","sequence":"additional","affiliation":[]},{"given":"Claire E.","family":"Kelly","sequence":"additional","affiliation":[]},{"given":"Sila","family":"Genc","sequence":"additional","affiliation":[]},{"given":"Joseph Yuan-Mou","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Ye","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Nagesh","family":"Adluru","sequence":"additional","affiliation":[]},{"given":"Vishwesh","family":"Nath","sequence":"additional","affiliation":[]},{"given":"Sudhir","family":"Pathak","sequence":"additional","affiliation":[]},{"given":"Walter","family":"Schneider","sequence":"additional","affiliation":[]},{"given":"Anurag","family":"Gade","sequence":"additional","affiliation":[]},{"given":"William","family":"Consagra","sequence":"additional","affiliation":[]},{"given":"Yogesh","family":"Rathi","sequence":"additional","affiliation":[]},{"given":"Tom","family":"Hendriks","sequence":"additional","affiliation":[]},{"given":"Anna","family":"Vilanova","sequence":"additional","affiliation":[]},{"given":"Maxime","family":"Chamberland","sequence":"additional","affiliation":[]},{"given":"Tomasz","family":"Pieciak","sequence":"additional","affiliation":[]},{"given":"Dominika","family":"Ciupek","sequence":"additional","affiliation":[]},{"given":"Antonio Trist\u00e1n","family":"Vega","sequence":"additional","affiliation":[]},{"given":"Santiago","family":"Aja-Fern\u00e1ndez","sequence":"additional","affiliation":[]},{"given":"Maciej","family":"Malawski","sequence":"additional","affiliation":[]},{"given":"Gani","family":"Ouedraogo","sequence":"additional","affiliation":[]},{"given":"Julia","family":"Machnio","sequence":"additional","affiliation":[]},{"given":"Paul M.","family":"Thompson","sequence":"additional","affiliation":[]},{"given":"Neda","family":"Jahanshad","sequence":"additional","affiliation":[]},{"given":"Eleftherios","family":"Garyfallidis","sequence":"additional","affiliation":[]},{"given":"Bennett","family":"Landman","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,18]]},"reference":[{"key":"15_CR1","doi-asserted-by":"publisher","unstructured":"Aganj, I., Lenglet, C., Sapiro, G.: Odf reconstruction in q-ball imaging with solid angle consideration. In: Proceedings\/IEEE International Symposium on Biomedical Imaging: From Nano to Macro. IEEE International Symposium on Biomedical Imaging 2009, vol. 1398 (2009). https:\/\/doi.org\/10.1109\/ISBI.2009.5193327","DOI":"10.1109\/ISBI.2009.5193327"},{"key":"15_CR2","doi-asserted-by":"publisher","unstructured":"Annett, M.: A classification of hand preference by association analysis. Brit. J. Psychol. 61, 303\u2013321 (1970). https:\/\/doi.org\/10.1111\/J.2044-8295.1970.TB01248.X","DOI":"10.1111\/J.2044-8295.1970.TB01248.X"},{"key":"15_CR3","doi-asserted-by":"publisher","unstructured":"Cetin-Karayumak, S., Zhang, F., O\u2019Donnell, L.J., Rathi, Y.: Harmonization of multi-site diffusion magnetic resonance imaging data from the adolescent brain cognitive development study. Biol. Psychiat. 91, S84 (2022). https:\/\/doi.org\/10.1016\/j.biopsych.2022.02.227","DOI":"10.1016\/j.biopsych.2022.02.227"},{"key":"15_CR4","doi-asserted-by":"crossref","unstructured":"Chandio, B.Q., Olivetti, E., Romero, D., Harezlak, J., Garyfallidis, E.: Bundlewarp, streamline-based nonlinear registration of white matter tracts. In: bioRxiv, pp. 2023\u201301 (2023)","DOI":"10.1101\/2023.01.04.522802"},{"key":"15_CR5","doi-asserted-by":"publisher","unstructured":"Chandio, B.Q., et al.: Bundle analytics, a computational framework for investigating the shapes and profiles of brain pathways across populations (2020). https:\/\/doi.org\/10.1038\/s41598-020-74054-4","DOI":"10.1038\/s41598-020-74054-4"},{"key":"15_CR6","doi-asserted-by":"publisher","unstructured":"Fischl, F.B.: Freesurfer (2012). https:\/\/doi.org\/10.1016\/j.neuroimage.2012.01.021","DOI":"10.1016\/j.neuroimage.2012.01.021"},{"key":"15_CR7","unstructured":"Garyfallidis, E.: Towards an accurate brain tractography [phd thesis]. University of Cambridge, United Kingdom (2012)"},{"key":"15_CR8","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/J.NICL.2017.08.017","volume":"17","author":"AS Heinsfeld","year":"2018","unstructured":"Heinsfeld, A.S., Franco, A.R., Craddock, R.C., Buchweitz, A., Meneguzzi, F.: Identification of autism spectrum disorder using deep learning and the abide dataset. NeuroImage: Clin. 17, 16 (2018). https:\/\/doi.org\/10.1016\/J.NICL.2017.08.017","journal-title":"NeuroImage: Clin."},{"key":"15_CR9","doi-asserted-by":"publisher","unstructured":"Jernigan, T.L., et al.: The pediatric imaging, neurocognition, and genetics (ping) data repository. NeuroImage 124, 1149 (2016). https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2015.04.057","DOI":"10.1016\/J.NEUROIMAGE.2015.04.057"},{"key":"15_CR10","doi-asserted-by":"publisher","unstructured":"Koo, T.K., Li, M.Y.: A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J. Chiropractic Med. 15, 155\u2013163 (2016). https:\/\/doi.org\/10.1016\/J.JCM.2016.02.012","DOI":"10.1016\/J.JCM.2016.02.012"},{"key":"15_CR11","doi-asserted-by":"publisher","unstructured":"Magnotta, V.A., et al.: Multicenter reliability of diffusion tensor imaging. Brain Connect. 2, 345 (2012). https:\/\/doi.org\/10.1089\/BRAIN.2012.0112","DOI":"10.1089\/BRAIN.2012.0112"},{"key":"15_CR12","doi-asserted-by":"publisher","unstructured":"Marcus, D.S., Wang, T.H., Parker, J., Csernansky, J.G., Morris, J.C., Buckner, R.L.: Open access series of imaging studies (oasis): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J. Cogn. Neurosci. 19, 1498\u20131507 (2007). https:\/\/doi.org\/10.1162\/JOCN.2007.19.9.1498","DOI":"10.1162\/JOCN.2007.19.9.1498"},{"key":"15_CR13","doi-asserted-by":"publisher","unstructured":"Ning, L., et al.: Muti-shell diffusion mri harmonisation and enhancement challenge (mushac): Progress and results. In: Mathematics and Visualization, pp. 217\u2013224 (2019). https:\/\/doi.org\/10.1007\/978-3-030-05831-9_18\/COVER","DOI":"10.1007\/978-3-030-05831-9_18\/COVER"},{"key":"15_CR14","doi-asserted-by":"publisher","unstructured":"Petersen, R.C., et al.: Alzheimer\u2019s disease neuroimaging initiative (adni): clinical characterization. Neurology 74, 201 (2010). https:\/\/doi.org\/10.1212\/WNL.0B013E3181CB3E25","DOI":"10.1212\/WNL.0B013E3181CB3E25"},{"key":"15_CR15","doi-asserted-by":"publisher","unstructured":"Pizzolato, M., Palombo, M., Hutter, J., Nash, V., Zhang, F., Gyori, N.: Super-resolution of multi dimensional diffusion mri data (2020). https:\/\/doi.org\/10.5281\/ZENODO.3718990","DOI":"10.5281\/ZENODO.3718990"},{"key":"15_CR16","doi-asserted-by":"publisher","unstructured":"Rubinov, M., Sporns, O.: Complex network measures of brain connectivity: uses and interpretations. NeuroImage 52, 1059\u20131069 (2010). https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2009.10.003","DOI":"10.1016\/J.NEUROIMAGE.2009.10.003"},{"key":"15_CR17","doi-asserted-by":"publisher","unstructured":"Schilling, K.G., et al.: Fiber tractography bundle segmentation depends on scanner effects, vendor effects, acquisition resolution, diffusion sampling scheme, diffusion sensitization, and bundle segmentation workflow. NeuroImage 242, 118451 (2021). https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2021.118451","DOI":"10.1016\/J.NEUROIMAGE.2021.118451"},{"key":"15_CR18","doi-asserted-by":"publisher","unstructured":"Somerville, L.H., et al.: The lifespan human connectome project in development: a large-scale study of brain connectivity development in 5\u201321 year olds. NeuroImage 183, 456 (2018). https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2018.08.050","DOI":"10.1016\/J.NEUROIMAGE.2018.08.050"},{"key":"15_CR19","doi-asserted-by":"publisher","unstructured":"Strike, L.T., et al.: queensland twin imaging (qtim) (2023). https:\/\/doi.org\/10.18112\/openneuro.ds004169.v1.0.7","DOI":"10.18112\/openneuro.ds004169.v1.0.7"},{"key":"15_CR20","doi-asserted-by":"publisher","unstructured":"Tax, C.M., et al.: Cross-scanner and cross-protocol diffusion mri data harmonisation: a benchmark database and evaluation of algorithms. NeuroImage 195, 285\u2013299 (2019). https:\/\/doi.org\/10.1016\/j.neuroimage.2019.01.077","DOI":"10.1016\/j.neuroimage.2019.01.077"},{"key":"15_CR21","doi-asserted-by":"publisher","unstructured":"Vollmar, C., et al.: Identical, but not the same: intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0 t scanners. NeuroImage 51, 1384\u20131394 (2010). https:\/\/doi.org\/10.1016\/J.NEUROIMAGE.2010.03.046","DOI":"10.1016\/J.NEUROIMAGE.2010.03.046"}],"container-title":["Lecture Notes in Computer Science","Computational Diffusion MRI"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-86920-4_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,17]],"date-time":"2025-04-17T08:58:08Z","timestamp":1744880288000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-86920-4_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031869198","9783031869204"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-86920-4_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"18 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CDMRI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Computational Diffusion MRI","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cdmri2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cmic.cs.ucl.ac.uk\/cdmri\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}