{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T17:13:02Z","timestamp":1774631582107,"version":"3.50.1"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031732928","type":"print"},{"value":"9783031732904","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T00:00:00Z","timestamp":1729641600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,23]],"date-time":"2024-10-23T00:00:00Z","timestamp":1729641600000},"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\/978-3-031-73290-4_13","type":"book-chapter","created":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T06:02:21Z","timestamp":1729576941000},"page":"128-137","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["StoDIP: Efficient 3D MRF Image Reconstruction with\u00a0Deep Image Priors and\u00a0Stochastic Iterations"],"prefix":"10.1007","author":[{"given":"Perla","family":"Mayo","sequence":"first","affiliation":[]},{"given":"Matteo","family":"Cencini","sequence":"additional","affiliation":[]},{"given":"Carolin M.","family":"Pirkl","sequence":"additional","affiliation":[]},{"given":"Marion I.","family":"Menzel","sequence":"additional","affiliation":[]},{"given":"Michela","family":"Tosetti","sequence":"additional","affiliation":[]},{"given":"Bjoern H.","family":"Menze","sequence":"additional","affiliation":[]},{"given":"Mohammad","family":"Golbabaee","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,23]]},"reference":[{"issue":"1","key":"13_CR1","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1002\/mrm.26639","volume":"79","author":"J Assl\u00e4nder","year":"2018","unstructured":"Assl\u00e4nder, J., et al.: Low rank alternating direction method of multipliers reconstruction for MR fingerprinting. Magn. Reson. Med. 79(1), 83\u201396 (2018)","journal-title":"Magn. Reson. Med."},{"key":"13_CR2","doi-asserted-by":"publisher","unstructured":"Cardoso, M.J., et\u00a0al.: MONAI: an open-source framework for deep learning in healthcare (2022). https:\/\/doi.org\/10.48550\/arXiv.2211.02701","DOI":"10.48550\/arXiv.2211.02701"},{"key":"13_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/978-3-030-59713-9_2","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","author":"D Chen","year":"2020","unstructured":"Chen, D., Davies, M.E., Golbabaee, M.: Compressive MR fingerprinting reconstruction with neural proximal gradient iterations. In: Martel, A.L., et al. (eds.) MICCAI 2020. LNCS, vol. 12262, pp. 13\u201322. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-59713-9_2"},{"key":"13_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116329","volume":"206","author":"Y Chen","year":"2020","unstructured":"Chen, Y., Fang, Z., Hung, S.C., Chang, W.T., Shen, D., Lin, W.: High-resolution 3D MR fingerprinting using parallel imaging and deep learning. Neuroimage 206, 116329 (2020)","journal-title":"Neuroimage"},{"issue":"3","key":"13_CR5","doi-asserted-by":"publisher","first-page":"885","DOI":"10.1002\/mrm.27198","volume":"80","author":"O Cohen","year":"2018","unstructured":"Cohen, O., Zhu, B., Rosen, M.S.: MR fingerprinting deep reconstruction network (drone). Magn. Reson. Med. 80(3), 885\u2013894 (2018)","journal-title":"Magn. Reson. Med."},{"issue":"4","key":"13_CR6","doi-asserted-by":"publisher","first-page":"2623","DOI":"10.1137\/130947246","volume":"7","author":"M Davies","year":"2014","unstructured":"Davies, M., Puy, G., Vandergheynst, P., Wiaux, Y.: A compressed sensing framework for magnetic resonance fingerprinting. SIAM J. Imag. Sci. 7(4), 2623\u20132656 (2014)","journal-title":"SIAM J. Imag. Sci."},{"issue":"10","key":"13_CR7","doi-asserted-by":"publisher","first-page":"2364","DOI":"10.1109\/TMI.2019.2899328","volume":"38","author":"Z Fang","year":"2019","unstructured":"Fang, Z., et al.: Deep learning for fast and spatially constrained tissue quantification from highly accelerated data in magnetic resonance fingerprinting. IEEE Trans. Med. Imaging 38(10), 2364\u20132374 (2019)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"13_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/978-3-030-32248-9_12","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2019","author":"Z Fang","year":"2019","unstructured":"Fang, Z., Chen, Y., Nie, D., Lin, W., Shen, D.: RCA-U-Net: residual channel attention U-net for fast tissue quantification in magnetic resonance fingerprinting. In: Shen, D., et al. (eds.) MICCAI 2019. LNCS, vol. 11766, pp. 101\u2013109. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-32248-9_12"},{"key":"13_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101945","volume":"69","author":"M Golbabaee","year":"2021","unstructured":"Golbabaee, M., et al.: Compressive MRI quantification using convex spatiotemporal priors and deep encoder-decoder networks. Med. Image Anal. 69, 101945 (2021)","journal-title":"Med. Image Anal."},{"issue":"1","key":"13_CR10","doi-asserted-by":"publisher","first-page":"8468","DOI":"10.1038\/s41598-019-44832-w","volume":"9","author":"PA G\u00f3mez","year":"2019","unstructured":"G\u00f3mez, P.A., Molina-Romero, M., Buonincontri, G., Menzel, M.I., Menze, B.H.: Designing contrasts for rapid, simultaneous parameter quantification and flow visualization with quantitative transient-state imaging. Sci. Rep. 9(1), 8468 (2019)","journal-title":"Sci. Rep."},{"issue":"7","key":"13_CR11","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/TMI.2018.2888491","volume":"38","author":"K Gong","year":"2018","unstructured":"Gong, K., Catana, C., Qi, J., Li, Q.: Pet image reconstruction using deep image prior. IEEE Trans. Med. Imaging 38(7), 1655\u20131665 (2018)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"13_CR12","doi-asserted-by":"publisher","DOI":"10.3389\/fcvm.2022.928546","volume":"9","author":"JI Hamilton","year":"2022","unstructured":"Hamilton, J.I.: A self-supervised deep learning reconstruction for shortening the breathhold and acquisition window in cardiac magnetic resonance fingerprinting. Front. Cardiovasc. Med. 9, 928546 (2022)","journal-title":"Front. Cardiovasc. Med."},{"issue":"4","key":"13_CR13","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1002\/jmrs.413","volume":"67","author":"JJ Hsieh","year":"2020","unstructured":"Hsieh, J.J., Svalbe, I.: Magnetic resonance fingerprinting: from evolution to clinical applications. J. Med. Radiat. Sci. 67(4), 333\u2013344 (2020)","journal-title":"J. Med. Radiat. Sci."},{"issue":"7440","key":"13_CR14","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1038\/nature11971","volume":"495","author":"D Ma","year":"2013","unstructured":"Ma, D., et al.: Magnetic resonance fingerprinting. Nature 495(7440), 187\u2013192 (2013)","journal-title":"Nature"},{"issue":"12","key":"13_CR15","doi-asserted-by":"publisher","first-page":"2311","DOI":"10.1109\/TMI.2014.2337321","volume":"33","author":"D McGivney","year":"2014","unstructured":"McGivney, D., et al.: SVD compression for magnetic resonance fingerprinting in the time domain. IEEE Trans. Med. Imaging 33(12), 2311\u20132322 (2014)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"13_CR16","unstructured":"Muckley, M.J., Stern, R., Murrell, T., Knoll, F.: TorchKbNufft: a high-level, hardware-agnostic non-uniform fast Fourier transform. In: ISMRM Workshop on Data Sampling & Image Reconstruction (2020). https:\/\/github.com\/mmuckley\/torchkbnufft"},{"issue":"3","key":"13_CR17","doi-asserted-by":"publisher","first-page":"675","DOI":"10.1002\/jmri.26836","volume":"51","author":"ME Poorman","year":"2020","unstructured":"Poorman, M.E., et al.: Magnetic resonance fingerprinting part 1: potential uses, current challenges, and recommendations. J. Magn. Reson. Imaging 51(3), 675\u2013692 (2020)","journal-title":"J. Magn. Reson. Imaging"},{"key":"13_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015, Part III. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"key":"13_CR19","doi-asserted-by":"crossref","unstructured":"Shih, Y.H., Wright, G., And\u00e9n, J., Blaschke, J., Barnett, A.H.: cuFINUFFT: a load-balanced GPU library for general-purpose nonuniform FFTS. In: 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 688\u2013697. IEEE (2021)","DOI":"10.1109\/IPDPSW52791.2021.00105"},{"issue":"3","key":"13_CR20","doi-asserted-by":"publisher","first-page":"143","DOI":"10.1002\/hbm.10062","volume":"17","author":"SM Smith","year":"2002","unstructured":"Smith, S.M.: Fast robust automated brain extraction. Hum. Brain Mapp. 17(3), 143\u2013155 (2002)","journal-title":"Hum. Brain Mapp."},{"key":"13_CR21","doi-asserted-by":"crossref","unstructured":"Ulyanov, D., Vedaldi, A., Lempitsky, V.: Deep image prior. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 9446\u20139454 (2018)","DOI":"10.1109\/CVPR.2018.00984"},{"key":"13_CR22","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1016\/j.neucom.2015.09.077","volume":"174","author":"Z Wang","year":"2016","unstructured":"Wang, Z., Li, H., Zhang, Q., Yuan, J., Wang, X.: Magnetic resonance fingerprinting with compressed sensing and distance metric learning. Neurocomputing 174, 560\u2013570 (2016)","journal-title":"Neurocomputing"},{"issue":"12","key":"13_CR23","doi-asserted-by":"publisher","first-page":"3337","DOI":"10.1109\/TMI.2021.3084288","volume":"40","author":"J Yoo","year":"2021","unstructured":"Yoo, J., Jin, K.H., Gupta, H., Yerly, J., Stuber, M., Unser, M.: Time-dependent deep image prior for dynamic MRI. IEEE Trans. Med. Imaging 40(12), 3337\u20133348 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"10","key":"13_CR24","doi-asserted-by":"publisher","first-page":"6360","DOI":"10.1109\/TPAMI.2021.3088914","volume":"44","author":"K Zhang","year":"2021","unstructured":"Zhang, K., Li, Y., Zuo, W., Zhang, L., Van Gool, L., Timofte, R.: Plug-and-play image restoration with deep denoiser prior. IEEE Trans. Pattern Anal. Mach. Intell. 44(10), 6360\u20136376 (2021)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"13_CR25","doi-asserted-by":"publisher","first-page":"933","DOI":"10.1002\/mrm.26701","volume":"79","author":"B Zhao","year":"2018","unstructured":"Zhao, B., et al.: Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling. Magn. Reson. Med. 79(2), 933\u2013942 (2018)","journal-title":"Magn. Reson. Med."},{"issue":"8","key":"13_CR26","doi-asserted-by":"publisher","first-page":"1812","DOI":"10.1109\/TMI.2016.2531640","volume":"35","author":"B Zhao","year":"2016","unstructured":"Zhao, B., Setsompop, K., Ye, H., Cauley, S.F., Wald, L.L.: Maximum likelihood reconstruction for magnetic resonance fingerprinting. IEEE Trans. Med. Imaging 35(8), 1812\u20131823 (2016)","journal-title":"IEEE Trans. Med. Imaging"}],"container-title":["Lecture Notes in Computer Science","Machine Learning in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73290-4_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,30]],"date-time":"2024-11-30T00:34:15Z","timestamp":1732926855000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73290-4_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,23]]},"ISBN":["9783031732928","9783031732904"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73290-4_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,23]]},"assertion":[{"value":"23 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that\u00a0are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MLMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Machine Learning in Medical Imaging","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":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 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":"mlmi-med2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/view\/mlmi2024","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}