{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,17]],"date-time":"2026-02-17T23:28:56Z","timestamp":1771370936215,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319675633","type":"print"},{"value":"9783319675640","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-67564-0_13","type":"book-chapter","created":{"date-parts":[[2017,9,11]],"date-time":"2017-09-11T12:50:54Z","timestamp":1505134254000},"page":"127-135","source":"Crossref","is-referenced-by-count":6,"title":["Reconstruction of 3D Cardiac MR Images from\u00a02D Slices Using Directional Total Variation"],"prefix":"10.1007","author":[{"given":"Nicolas","family":"Basty","sequence":"first","affiliation":[]},{"given":"Darryl","family":"McClymont","sequence":"additional","affiliation":[]},{"given":"Irvin","family":"Teh","sequence":"additional","affiliation":[]},{"given":"J\u00fcrgen E.","family":"Schneider","sequence":"additional","affiliation":[]},{"given":"Vicente","family":"Grau","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,9]]},"reference":[{"key":"13_CR1","doi-asserted-by":"crossref","unstructured":"Bogaert, J., Dymarkowski, S., Taylor, A.M.: Clinical Cardiac MRI. Taylor & Francis US (2005)","DOI":"10.1007\/b138447"},{"issue":"6","key":"13_CR2","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1002\/mrm.21391","volume":"58","author":"M Lustig","year":"2007","unstructured":"Lustig, M., Donoho, D., Pauly, J.M.: Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn. Reson. Med. 58(6), 1182\u20131195 (2007)","journal-title":"Magn. Reson. Med."},{"issue":"4","key":"13_CR3","doi-asserted-by":"crossref","first-page":"979","DOI":"10.1109\/TMI.2014.2301271","volume":"33","author":"J Caballero","year":"2014","unstructured":"Caballero, J., Price, A.N., Rueckert, D., Hajnal, J.V.: Dictionary learning and time sparsity for dynamic MR data reconstruction. IEEE Trans. Med. Imaging 33(4), 979\u201394 (2014)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"5","key":"13_CR4","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1016\/S0730-725X(02)00511-8","volume":"20","author":"H Greenspan","year":"2002","unstructured":"Greenspan, H., Oz, G., Kiryati, N., Peled, S.: MRI inter-slice reconstruction using super-resolution. Magn. Reson. Imaging 20(5), 437\u2013446 (2002)","journal-title":"Magn. Reson. Imaging"},{"issue":"6","key":"13_CR5","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1002\/cmr.a.21249","volume":"40A","author":"E Reeth Van","year":"2012","unstructured":"Van Reeth, E., Tham, I.: Superresolution in magnetic resonance imaging: a review. Concepts Magn. Reson. Part A 40A(6), 306\u2013325 (2012)","journal-title":"Concepts Magn. Reson. Part A"},{"issue":"12","key":"13_CR6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TBME.2012.2228513","volume":"59","author":"J Woo","year":"2012","unstructured":"Woo, J., Murano, E., Stone, M., Prince, J.: Reconstruction of high resolution tongue volumes from MRI. IEEE Trans. Biomed. Eng. 59(12), 1\u20131 (2012)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"13_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1007\/978-3-642-15705-9_75","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2010","author":"DHJ Poot","year":"2010","unstructured":"Poot, D.H.J., Meir, V., Sijbers, J.: General and efficient super-resolution method for multi-slice MRI. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010. LNCS, vol. 6361, pp. 615\u2013622. Springer, Heidelberg (2010). doi: 10.1007\/978-3-642-15705-9_75"},{"issue":"6","key":"13_CR8","doi-asserted-by":"crossref","first-page":"1983","DOI":"10.1002\/mrm.24187","volume":"68","author":"E Plenge","year":"2012","unstructured":"Plenge, E., Poot, D.H.J., Bernsen, M., Kotek, G., Houston, G., Wielopolski, P., Van Der Weerd, L., Niessen, W.J., Meijering, E.: Super-resolution methods in MRI: can they improve the trade-off between resolution, signal-to-noise ratio, and acquisition time? Magn. Reson. Med. 68(6), 1983\u20131993 (2012)","journal-title":"Magn. Reson. Med."},{"key":"13_CR9","doi-asserted-by":"crossref","unstructured":"Khmelinskii, A., Plenge, E., Kok, P., Dzyubachyk, O., Poot, D.H.J., Suidgeest, E., Botha, C.P., Niessen, W.J., van der Weerd, L., Meijering, E., et al.: Super-resolution reconstruction of whole-body MRI mouse data: an interactive approach. In: 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1723\u20131726. IEEE (2012)","DOI":"10.1109\/ISBI.2012.6235912"},{"issue":"1\u20134","key":"13_CR10","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/0167-2789(92)90242-F","volume":"60","author":"LI Rudin","year":"1992","unstructured":"Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D 60(1\u20134), 259\u2013268 (1992)","journal-title":"Physica D"},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Joshi, S.H., Marquina, A., Osher, S.J., Dinov, I., Van Horn, J.D., Toga, A.W.: MRI resolution enhancement using total variation regularization. In: 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, pp. 161\u2013164. IEEE (2009)","DOI":"10.1109\/ISBI.2009.5193008"},{"issue":"3","key":"13_CR12","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1137\/15M1047325","volume":"9","author":"MJ Ehrhardt","year":"2016","unstructured":"Ehrhardt, M.J., Betcke, M.M.: Multicontrast MRI reconstruction with structure-guided total variation. SIAM J. Imaging Sci. 9(3), 1084\u20131106 (2016)","journal-title":"SIAM J. Imaging Sci."},{"key":"13_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"435","DOI":"10.1007\/978-3-319-24574-4_52","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"F Odille","year":"2015","unstructured":"Odille, F., Bustin, A., Chen, B., Vuissoz, P.-A., Felblinger, J.: Motion-corrected, super-resolution reconstruction for high-resolution 3D cardiac cine MRI. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 435\u2013442. Springer, Cham (2015). doi: 10.1007\/978-3-319-24574-4_52"},{"key":"13_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"246","DOI":"10.1007\/978-3-319-46726-9_29","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2016","author":"O Oktay","year":"2016","unstructured":"Oktay, O., et al.: Multi-input cardiac image super-resolution using convolutional neural networks. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9902, pp. 246\u2013254. Springer, Cham (2016). doi: 10.1007\/978-3-319-46726-9_29"},{"key":"13_CR15","unstructured":"Shewchuk, J.R.: An introduction to the conjugate gradient method without the agonizing pain (1994)"},{"key":"13_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1007\/978-3-319-10593-2_13","volume-title":"Computer Vision \u2013 ECCV 2014","author":"C Dong","year":"2014","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8692, pp. 184\u2013199. Springer, Cham (2014). doi: 10.1007\/978-3-319-10593-2_13"},{"key":"13_CR17","doi-asserted-by":"crossref","unstructured":"Oktay, O., Ferrante, E., Kamnitsas, K., Heinrich, M., Bai, W., Caballero, J., Guerrero, R., Cook, S., de Marvao, A., O\u2019Regan, D., et al.: Anatomically constrained neural networks (ACNN): application to cardiac image enhancement and segmentation. arXiv preprint arXiv:1705.08302 (2017)","DOI":"10.1109\/TMI.2017.2743464"}],"container-title":["Lecture Notes in Computer Science","Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-67564-0_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,3]],"date-time":"2019-10-03T05:37:06Z","timestamp":1570081026000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-67564-0_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319675633","9783319675640"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-67564-0_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]}}}