乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T23:19:25Z","timestamp":1725664765053},"reference-count":95,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,1,20]],"date-time":"2023-01-20T00:00:00Z","timestamp":1674172800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Medical Image Analysis"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1016\/j.media.2023.102744","type":"journal-article","created":{"date-parts":[[2023,1,19]],"date-time":"2023-01-19T20:17:43Z","timestamp":1674159463000},"page":"102744","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":7,"special_numbering":"C","title":["Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat)"],"prefix":"10.1016","volume":"86","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-4239-7192","authenticated-orcid":false,"given":"Ziyu","family":"Li","sequence":"first","affiliation":[]},{"given":"Qiuyun","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Berkin","family":"Bilgic","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-4677-1041","authenticated-orcid":false,"given":"Guangzhi","family":"Wang","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-5020-5165","authenticated-orcid":false,"given":"Wenchuan","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-1348-1179","authenticated-orcid":false,"given":"Jonathan R.","family":"Polimeni","sequence":"additional","affiliation":[]},{"given":"Karla L.","family":"Miller","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0003-2950-7254","authenticated-orcid":false,"given":"Susie Y.","family":"Huang","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-8350-5295","authenticated-orcid":false,"given":"Qiyuan","family":"Tian","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.media.2023.102744_bib0001","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.neuroimage.2017.02.089","article-title":"Image quality transfer and applications in diffusion MRI","volume":"152","author":"Alexander","year":"2017","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0002","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.neuroimage.2017.10.034","article-title":"Image processing and quality control for the first 10,000 brain imaging datasets from UK Biobank","volume":"166","author":"Alfaro-Almagro","year":"2018","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1101\/lm.43402","article-title":"Alterations in the thickness of motor cortical subregions after motor-skill learning and exercise","volume":"9","author":"Anderson","year":"2002","journal-title":"Learn. Memory"},{"key":"10.1016\/j.media.2023.102744_bib0004","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.neuroimage.2017.12.040","article-title":"Susceptibility-induced distortion that varies due to motion: correction in diffusion MR without acquiring additional data","volume":"171","author":"Andersson","year":"2018","journal-title":"Neuroimage"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0005","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1016\/S1053-8119(03)00336-7","article-title":"How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging","volume":"20","author":"Andersson","year":"2003","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0006","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1016\/j.neuroimage.2015.10.019","article-title":"An integrated approach to correction for off-resonance effects and subject movement in diffusion MR imaging","volume":"125","author":"Andersson","year":"2016","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.compmedimag.2019.101684","article-title":"MedGAN: medical image translation using GANs","volume":"79","author":"Armanious","year":"2020","journal-title":"Comput. Med. Imaging Graph."},{"issue":"365","key":"10.1016\/j.media.2023.102744_bib0008","first-page":"1","article-title":"Advanced normalization tools (ANTS)","volume":"2","author":"Avants","year":"2009","journal-title":"Insight J."},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0009","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/S0006-3495(94)80775-1","article-title":"MR diffusion tensor spectroscopy and imaging","volume":"66","author":"Basser","year":"1994","journal-title":"Biophys. J."},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0010","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0247343","article-title":"Avoiding data loss: synthetic MRIs generated from diffusion imaging can replace corrupted structural acquisitions for freesurfer-seeded tractography","volume":"17","author":"Beaumont","year":"2022","journal-title":"PLoS One"},{"issue":"5","key":"10.1016\/j.media.2023.102744_bib0011","doi-asserted-by":"crossref","first-page":"1077","DOI":"10.1002\/mrm.10609","article-title":"Characterization and propagation of uncertainty in diffusion-weighted MR imaging","volume":"50","author":"Behrens","year":"2003","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2023.102744_bib0012","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.neuroimage.2015.03.050","article-title":"Co-registration and distortion correction of diffusion and anatomical images based on inverse contrast normalization","volume":"115","author":"Bhushan","year":"2015","journal-title":"Neuroimage"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0013","doi-asserted-by":"crossref","first-page":"1343","DOI":"10.1002\/mrm.27813","article-title":"Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction","volume":"82","author":"Bilgic","year":"2019","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2023.102744_bib0014","article-title":"Synthseg: domain randomisation for segmentation of brain mri scans of any contrast and resolution","author":"Billot","year":"2021","journal-title":"ArXiv"},{"key":"10.1016\/j.media.2023.102744_bib0015","doi-asserted-by":"crossref","first-page":"335","DOI":"10.1016\/j.neuroimage.2018.10.009","article-title":"The Lifespan Human Connectome Project in Aging: an overview","volume":"185","author":"Bookheimer","year":"2019","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0016","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.mri.2020.02.010","article-title":"Segmentation of the brain using direction-averaged signal of DWI images","volume":"69","author":"Cheng","year":"2020","journal-title":"Magn. Reson. Imaging"},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0017","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.2967\/jnumed.117.199414","article-title":"Generation of structural MR images from amyloid PET: application to MR-less quantification","volume":"59","author":"Choi","year":"2018","journal-title":"J. Nucl. Med."},{"key":"10.1016\/j.media.2023.102744_bib0018","series-title":"Paper presented at the International conference on medical image computing and computer-assisted intervention","article-title":"3D U-Net: learning dense volumetric segmentation from sparse annotation","author":"\u00c7i\u00e7ek","year":"2016"},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0019","doi-asserted-by":"crossref","first-page":"e3931","DOI":"10.1002\/nbm.3931","article-title":"Automated pixel-wise brain tissue segmentation of diffusion-weighted images via machine learning","volume":"31","author":"Ciritsis","year":"2018","journal-title":"NMR Biomed."},{"issue":"18","key":"10.1016\/j.media.2023.102744_bib0020","doi-asserted-by":"crossref","first-page":"10422","DOI":"10.1073\/pnas.96.18.10422","article-title":"Tracking neuronal fiber pathways in the living human brain","volume":"96","author":"Conturo","year":"1999","journal-title":"Proc. Natl. Acad. Sci."},{"issue":"12","key":"10.1016\/j.media.2023.102744_bib0021","doi-asserted-by":"crossref","first-page":"6343","DOI":"10.1002\/mp.14539","article-title":"Multimodal MRI synthesis using unified generative adversarial networks","volume":"47","author":"Dai","year":"2020","journal-title":"Med. Phys."},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0022","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1006\/nimg.1998.0395","article-title":"Cortical surface-based analysis: I. segmentation and surface reconstruction","volume":"9","author":"Dale","year":"1999","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0023","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2020.117206","article-title":"Spherical deconvolution with tissue-specific response functions and multi-shell diffusion MRI to estimate multiple fiber orientation distributions (mFODs)","volume":"222","author":"De Luca","year":"2020","journal-title":"Neuroimage"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0024","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","article-title":"Image super-resolution using deep convolutional networks","volume":"38","author":"Dong","year":"2016","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0025","doi-asserted-by":"crossref","first-page":"640","DOI":"10.1056\/NEJMoa1300962","article-title":"A pilot study of focused ultrasound thalamotomy for essential tremor","volume":"369","author":"Elias","year":"2013","journal-title":"N. Engl. J. Med."},{"issue":"8","key":"10.1016\/j.media.2023.102744_bib0026","doi-asserted-by":"crossref","first-page":"3627","DOI":"10.1002\/mp.13047","article-title":"Generating synthetic CTs from magnetic resonance images using generative adversarial networks","volume":"45","author":"Emami","year":"2018","journal-title":"Med. Phys."},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0027","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1038\/s41592-018-0261-2","article-title":"U-Net: deep learning for cell counting, detection, and morphometry","volume":"16","author":"Falk","year":"2019","journal-title":"Nat. Methods"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0029","doi-asserted-by":"crossref","first-page":"774","DOI":"10.1016\/j.neuroimage.2012.01.021","article-title":"FreeSurfer","volume":"62","author":"Fischl","year":"2012","journal-title":"Neuroimage"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0030","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1006\/nimg.1998.0396","article-title":"Cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system","volume":"9","author":"Fischl","year":"1999","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0032","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.neuroimage.2013.12.012","article-title":"Quantitative comparison of cortical surface reconstructions from MP2RAGE and multi-echo MPRAGE data at 3 and 7 T","volume":"90","author":"Fujimoto","year":"2014","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0033","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.neuroimage.2013.04.127","article-title":"The minimal preprocessing pipelines for the Human Connectome Project","volume":"80","author":"Glasser","year":"2013","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0034","unstructured":"Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Bengio, Y. (2014). Generative adversarial nets. Paper presented at the advances in neural information processing systems."},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0036","doi-asserted-by":"crossref","first-page":"180","DOI":"10.1016\/j.neuroimage.2006.02.051","article-title":"Reliability of MRI-derived measurements of human cerebral cortical thickness: the effects of field strength, scanner upgrade and manufacturer","volume":"32","author":"Han","year":"2006","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0037","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1016\/j.neuroimage.2018.09.060","article-title":"Extending the Human Connectome Project across ages: imaging protocols for the Lifespan Development and Aging projects","volume":"183","author":"Harms","year":"2018","journal-title":"Neuroimage"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0038","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1002\/mrm.27488","article-title":"Motion-robust reconstruction of multishot diffusion-weighted images without phase estimation through locally low-rank regularization","volume":"81","author":"Hu","year":"2019","journal-title":"Magn. Reson. Med."},{"issue":"5","key":"10.1016\/j.media.2023.102744_bib0039","doi-asserted-by":"crossref","first-page":"1596","DOI":"10.1002\/mrm.28025","article-title":"Multi-shot diffusion-weighted MRI reconstruction with magnitude-based spatial-angular locally low-rank regularization (SPA-LLR)","volume":"83","author":"Hu","year":"2020","journal-title":"Magn. Reson. Med."},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0040","doi-asserted-by":"crossref","first-page":"giy082","DOI":"10.1093\/gigascience\/giy082","article-title":"Nighres: processing tools for high-resolution neuroimaging","volume":"7","author":"Huntenburg","year":"2018","journal-title":"Gigascience"},{"key":"10.1016\/j.media.2023.102744_bib0041","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118206","article-title":"Joint super-resolution and synthesis of 1mm isotropic MP-RAGE volumes from clinical MRI exams with scans of different orientation, resolution and contrast","author":"Iglesias","year":"2021","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0042","series-title":"Paper presented at the Proceedings of the IEEE conference on computer vision and pattern recognition","article-title":"Image-to-image translation with conditional adversarial networks","author":"Isola","year":"2017"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0043","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1002\/jmri.21049","article-title":"The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods","volume":"27","author":"Jack Jr","year":"2008","journal-title":"J. Magn. Reson. Imaging"},{"issue":"6","key":"10.1016\/j.media.2023.102744_bib0044","doi-asserted-by":"crossref","first-page":"1846","DOI":"10.1002\/mrm.24204","article-title":"Model-based analysis of multishell diffusion MR data for tractography: how to get over fitting problems","volume":"68","author":"Jbabdi","year":"2012","journal-title":"Magn. Reson. Med."},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0045","doi-asserted-by":"crossref","first-page":"782","DOI":"10.1016\/j.neuroimage.2011.09.015","article-title":"FSL","volume":"62","author":"Jenkinson","year":"2012","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0046","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/j.neuroimage.2014.07.061","article-title":"Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data","volume":"103","author":"Jeurissen","year":"2014","journal-title":"Neuroimage"},{"issue":"9","key":"10.1016\/j.media.2023.102744_bib0047","doi-asserted-by":"crossref","first-page":"566","DOI":"10.1007\/s11604-018-0758-8","article-title":"Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network","volume":"36","author":"Jiang","year":"2018","journal-title":"Jpn. J. Radiol."},{"issue":"3","key":"10.1016\/j.media.2023.102744_bib0049","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s12194-019-00520-y","article-title":"Overview of image-to-image translation by use of deep neural networks: denoising, super-resolution, modality conversion, and reconstruction in medical imaging","volume":"12","author":"Kaji","year":"2019","journal-title":"Radiol. Phys. Technol."},{"key":"10.1016\/j.media.2023.102744_bib0051","series-title":"2016 IEEE Conference on Computer Vision and Pattern Recognition","first-page":"1646","article-title":"Accurate image super-resolution using very deep convolutional networks","author":"Kim","year":"2016"},{"key":"10.1016\/j.media.2023.102744_bib0052","article-title":"Adam: a method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"ArXiv"},{"key":"10.1016\/j.media.2023.102744_bib0053","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2021.104297","article-title":"MPRAGE to MP2RAGE UNI translation via generative adversarial network improves the automatic tissue and lesion segmentation in multiple sclerosis patients","volume":"132","author":"La Rosa","year":"2021","journal-title":"Comput. Biol. Med."},{"key":"10.1016\/j.media.2023.102744_bib0054","series-title":"IEEE Conference on Computer Vision and Pattern Recognition","first-page":"4681","article-title":"Photo-realistic single image super-resolution using a generative adversarial network","author":"Ledig","year":"2017"},{"key":"10.1016\/j.media.2023.102744_bib0055","series-title":"30th IEEE Conference on Computer Vision and Pattern Recognition","first-page":"105","article-title":"Photo-realistic single image super-resolution using a generative adversarial network","author":"Ledig","year":"2017"},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0056","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1093\/cercor\/bhh200","article-title":"Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy","volume":"15","author":"Lerch","year":"2005","journal-title":"Cereb. Cortex"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0057","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1002\/mp.15427","article-title":"High\u2010fidelity fast volumetric brain MRI using synergistic wave\u2010controlled aliasing in parallel imaging and a hybrid denoising generative adversarial network (HDnGAN)","volume":"49","author":"Li","year":"2022","journal-title":"Medical Physics"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0058","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1002\/mrm.28748","article-title":"Distortion-free, high-isotropic-resolution diffusion MRI with gSlider BUDA-EPI and multicoil dynamic B0 shimming","volume":"86","author":"Liao","year":"2021","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2023.102744_bib0059","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.118105","article-title":"Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy","volume":"237","author":"Little","year":"2021","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0060","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.neuroimage.2007.07.002","article-title":"Brain tissue segmentation based on DTI data","volume":"38","author":"Liu","year":"2007","journal-title":"Neuroimage"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0061","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1002\/nbm.1020","article-title":"Three-dimensional characterization of non-gaussian water diffusion in humans using diffusion kurtosis imaging","volume":"19","author":"Lu","year":"2006","journal-title":"NMR Biomed."},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0062","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1016\/j.pneurobio.2011.09.005","article-title":"The parkinson progression marker initiative (PPMI)","volume":"95","author":"Marek","year":"2011","journal-title":"Prog. Neurobiol."},{"key":"10.1016\/j.media.2023.102744_bib0063","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1016\/j.neuroimage.2013.05.074","article-title":"The Human Connectome Project and beyond: initial applications of 300 mT\/m gradients","volume":"80","author":"McNab","year":"2013","journal-title":"Neuroimage"},{"issue":"11","key":"10.1016\/j.media.2023.102744_bib0065","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1038\/nn.4393","article-title":"Multimodal population brain imaging in the UK Biobank prospective epidemiological study","volume":"19","author":"Miller","year":"2016","journal-title":"Nat. Neurosci."},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0068","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1002\/1531-8249(199902)45:2<265::AID-ANA21>3.0.CO;2-3","article-title":"Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging","volume":"45","author":"Mori","year":"1999","journal-title":"Ann. Neurol."},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0069","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1016\/j.nic.2005.09.008","article-title":"The Alzheimer's disease neuroimaging initiative","volume":"15","author":"Mueller","year":"2005","journal-title":"Neuroimaging Clin. N. Am."},{"key":"10.1016\/j.media.2023.102744_bib0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2020.116835","article-title":"SANDI: a compartment-based model for non-invasive apparent soma and neurite imaging by diffusion MRI","volume":"215","author":"Palombo","year":"2020","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0071","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.neuroimage.2011.02.076","article-title":"Avoiding asymmetry-induced bias in longitudinal image processing","volume":"57","author":"Reuter","year":"2011","journal-title":"Neuroimage"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0072","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1016\/j.neuroimage.2010.07.020","article-title":"Highly accurate inverse consistent registration: a robust approach","volume":"53","author":"Reuter","year":"2010","journal-title":"Neuroimage"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0073","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.1016\/j.neuroimage.2012.02.084","article-title":"Within-subject template estimation for unbiased longitudinal image analysis","volume":"61","author":"Reuter","year":"2012","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0074","series-title":"Paper presented at the International Conference on Medical Image Computing and Computer-Assisted Intervention","article-title":"U-net: convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"issue":"8","key":"10.1016\/j.media.2023.102744_bib0075","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1016\/j.neurobiolaging.2004.09.017","article-title":"Age-related alterations in white matter microstructure measured by diffusion tensor imaging","volume":"26","author":"Salat","year":"2005","journal-title":"Neurobiol. Aging"},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0077","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1093\/cercor\/bhh032","article-title":"Thinning of the cerebral cortex in aging","volume":"14","author":"Salat","year":"2004","journal-title":"Cereb. Cortex"},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0078","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0236418","article-title":"Distortion correction of diffusion weighted MRI without reverse phase-encoding scans or field-maps","volume":"15","author":"Schilling","year":"2020","journal-title":"PLoS One"},{"key":"10.1016\/j.media.2023.102744_bib0079","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.mri.2019.05.008","article-title":"Synthesized b0 for diffusion distortion correction (Synb0-DisCo)","volume":"64","author":"Schilling","year":"2019","journal-title":"Magn. Reson. Imaging"},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0080","doi-asserted-by":"crossref","first-page":"569","DOI":"10.1016\/j.neuroimage.2012.06.033","article-title":"Improving diffusion MRI using simultaneous multi-slice echo planar imaging","volume":"63","author":"Setsompop","year":"2012","journal-title":"Neuroimage"},{"issue":"5","key":"10.1016\/j.media.2023.102744_bib0081","doi-asserted-by":"crossref","first-page":"1210","DOI":"10.1002\/mrm.23097","article-title":"Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty","volume":"67","author":"Setsompop","year":"2012","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2023.102744_bib0083","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"ArXiv"},{"issue":"2","key":"10.1016\/j.media.2023.102744_bib0084","doi-asserted-by":"crossref","first-page":"340","DOI":"10.1006\/jmre.2000.2209","article-title":"Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI","volume":"147","author":"Skare","year":"2000","journal-title":"J. Magn. Reson."},{"issue":"3","key":"10.1016\/j.media.2023.102744_bib0085","doi-asserted-by":"crossref","first-page":"1924","DOI":"10.1016\/j.neuroimage.2012.06.005","article-title":"Anatomically-constrained tractography: improved diffusion MRI streamlines tractography through effective use of anatomical information","volume":"62","author":"Smith","year":"2012","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0086","doi-asserted-by":"crossref","first-page":"S208","DOI":"10.1016\/j.neuroimage.2004.07.051","article-title":"Advances in functional and structural MR image analysis and implementation as FSL","volume":"23","author":"Smith","year":"2004","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0087","doi-asserted-by":"crossref","first-page":"456","DOI":"10.1016\/j.neuroimage.2018.08.050","article-title":"The Lifespan Human Connectome Project in Development: a large-scale study of brain connectivity development in 5\u201321 year olds","volume":"183","author":"Somerville","year":"2018","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0088","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.neuroimage.2013.05.057","article-title":"Advances in diffusion MRI acquisition and processing in the Human Connectome Project","volume":"80","author":"Sotiropoulos","year":"2013","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0089","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2020.117017","article-title":"DeepDTI: high-fidelity six-direction diffusion tensor imaging using deep learning","volume":"219","author":"Tian","year":"2020","journal-title":"Neuroimage"},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0091","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1093\/cercor\/bhaa237","article-title":"Improving in vivo human cerebral cortical surface reconstruction using data-driven super-resolution","volume":"31","author":"Tian","year":"2020","journal-title":"Cereb. Cortex"},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0092","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1038\/s41597-021-01092-6","article-title":"Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT\/m gradients","volume":"9","author":"Tian","year":"2022","journal-title":"Sci. Data"},{"key":"10.1016\/j.media.2023.102744_bib0093","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2022.119033","article-title":"SDnDTI: self-supervised deep learning-based denoising for diffusion tensor MRI","volume":"253","author":"Tian","year":"2022","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0094","doi-asserted-by":"crossref","first-page":"572","DOI":"10.1016\/j.nicl.2018.05.010","article-title":"Diffusion MRI tractography for improved transcranial MRI-guided focused ultrasound thalamotomy targeting for essential tremor","volume":"19","author":"Tian","year":"2018","journal-title":"Neuroimage Clin."},{"key":"10.1016\/j.media.2023.102744_bib0095","doi-asserted-by":"crossref","first-page":"497","DOI":"10.1016\/j.neuroimage.2019.01.038","article-title":"Generalized diffusion spectrum magnetic resonance imaging (GDSI) for model-free reconstruction of the ensemble average propagator","volume":"189","author":"Tian","year":"2019","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0096","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.117946","article-title":"Improved cortical surface reconstruction using sub-millimeter resolution MPRAGE by image denoising","volume":"233","author":"Tian","year":"2021","journal-title":"Neuroimage"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0097","doi-asserted-by":"crossref","first-page":"1459","DOI":"10.1016\/j.neuroimage.2007.02.016","article-title":"Robust determination of the fibre orientation distribution in diffusion MRI: non-negativity constrained super-resolved spherical deconvolution","volume":"35","author":"Tournier","year":"2007","journal-title":"Neuroimage"},{"issue":"3","key":"10.1016\/j.media.2023.102744_bib0098","doi-asserted-by":"crossref","first-page":"1176","DOI":"10.1016\/j.neuroimage.2004.07.037","article-title":"Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution","volume":"23","author":"Tournier","year":"2004","journal-title":"Neuroimage"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0099","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1002\/mrm.10268","article-title":"High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity","volume":"48","author":"Tuch","year":"2002","journal-title":"Magn. Reson. Med."},{"issue":"6","key":"10.1016\/j.media.2023.102744_bib0101","doi-asserted-by":"crossref","first-page":"1377","DOI":"10.1002\/mrm.20642","article-title":"Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging","volume":"54","author":"Wedeen","year":"2005","journal-title":"Magn. Reson. Med."},{"key":"10.1016\/j.media.2023.102744_bib0102","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2020.101944","article-title":"Mustgan: multi-stream generative adversarial networks for MR image synthesis","volume":"70","author":"Yurt","year":"2021","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2023.102744_bib0103","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.neuroimage.2017.09.060","article-title":"Advantages of cortical surface reconstruction using submillimeter 7 T MEMPRAGE","volume":"165","author":"Zaretskaya","year":"2018","journal-title":"Neuroimage"},{"key":"10.1016\/j.media.2023.102744_bib0104","doi-asserted-by":"crossref","DOI":"10.1016\/j.neuroimage.2021.117934","article-title":"Deep learning based segmentation of brain tissue from diffusion MRI","volume":"233","author":"Zhang","year":"2021","journal-title":"Neuroimage"},{"issue":"4","key":"10.1016\/j.media.2023.102744_bib0105","doi-asserted-by":"crossref","first-page":"1000","DOI":"10.1016\/j.neuroimage.2012.03.072","article-title":"NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain","volume":"61","author":"Zhang","year":"2012","journal-title":"Neuroimage"},{"issue":"7","key":"10.1016\/j.media.2023.102744_bib0106","doi-asserted-by":"crossref","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","article-title":"Beyond a gaussian denoiser: residual learning of deep cnn for image denoising","volume":"26","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"10.1016\/j.media.2023.102744_bib0107","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1117\/1.1527628","article-title":"Level set modeling and segmentation of diffusion tensor magnetic resonance imaging brain data","volume":"12","author":"Zhukov","year":"2003","journal-title":"J. Electron. Imaging"}],"container-title":["Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841523000051?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841523000051?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,5,16]],"date-time":"2024-05-16T12:07:51Z","timestamp":1715861271000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1361841523000051"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5]]},"references-count":95,"alternative-id":["S1361841523000051"],"URL":"https:\/\/doi.org\/10.1016\/j.media.2023.102744","relation":{},"ISSN":["1361-8415"],"issn-type":[{"value":"1361-8415","type":"print"}],"subject":[],"published":{"date-parts":[[2023,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat)","name":"articletitle","label":"Article Title"},{"value":"Medical Image Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.media.2023.102744","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"102744"}}