{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T07:25:17Z","timestamp":1775460317068,"version":"3.50.1"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030009274","type":"print"},{"value":"9783030009281","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-030-00928-1_17","type":"book-chapter","created":{"date-parts":[[2018,9,13]],"date-time":"2018-09-13T03:00:42Z","timestamp":1536807642000},"page":"145-153","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":52,"title":["Some Investigations on Robustness of Deep Learning in Limited Angle Tomography"],"prefix":"10.1007","author":[{"given":"Yixing","family":"Huang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tobias","family":"W\u00fcrfl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katharina","family":"Breininger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ling","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"G\u00fcnter","family":"Lauritsch","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andreas","family":"Maier","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,26]]},"reference":[{"issue":"7","key":"17_CR1","doi-asserted-by":"publisher","first-page":"2119","DOI":"10.1088\/0031-9155\/58\/7\/2119","volume":"58","author":"Z Chen","year":"2013","unstructured":"Chen, Z., Jin, X., Li, L., Wang, G.: A limited-angle $$\\text{ CT }$$ reconstruction method based on anisotropic $$\\text{ TV }$$ minimization. Phys. Med. Biol. 58(7), 2119\u20132141 (2013)","journal-title":"Phys. Med. Biol."},{"key":"17_CR2","unstructured":"Evtimov, I., et al.: Robust physical-world attacks on deep learning models. arXiv preprint 1 (2017)"},{"key":"17_CR3","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. arXiv preprint (2014)"},{"key":"17_CR4","unstructured":"Gu, J., Ye, J.C.: Multi-scale wavelet domain residual learning for limited-angle CT reconstruction. In: Proceedings of Fully3D, pp. 443\u2013447 (2017)"},{"key":"17_CR5","series-title":"Informatik aktuell","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1007\/978-3-662-54345-0_25","volume-title":"Bildverarbeitung f\u00fcr die Medizin 2017","author":"K Hammernik","year":"2017","unstructured":"Hammernik, K., W\u00fcrfl, T., Pock, T., Maier, A.: A deep learning architecture for limited-angle computed tomography reconstruction. In: Maier-Hein, K.H., Deserno, T.M., Handels, H., Tolxdorff, T. (eds.) Bildverarbeitung f\u00fcr die Medizin 2017. Informatik aktuell, pp. 92\u201397. Springer, Heidelberg (2017). https:\/\/doi.org\/10.1007\/978-3-662-54345-0_25"},{"issue":"3","key":"17_CR6","doi-asserted-by":"publisher","first-page":"035015","DOI":"10.1088\/2057-1976\/aa71bf","volume":"3","author":"Y Huang","year":"2017","unstructured":"Huang, Y., et al.: Restoration of missing data in limited angle tomography based on Helgason-Ludwig consistency conditions. Biomed. Phys. Eng. Express 3(3), 035015 (2017)","journal-title":"Biomed. Phys. Eng. Express"},{"key":"17_CR7","unstructured":"Kurakin, A., Goodfellow, I., Bengio, S.: Adversarial examples in the physical world. arXiv preprint (2016)"},{"key":"17_CR8","doi-asserted-by":"crossref","unstructured":"Maier, A., et al.: Precision learning: towards use of known operators in neural networks. In: International Conference on Pattern Recognition (2018, to appear). https:\/\/arxiv.org\/abs\/1712.00374","DOI":"10.1109\/ICPR.2018.8545553"},{"issue":"10","key":"17_CR9","doi-asserted-by":"publisher","first-page":"e3","DOI":"10.23915\/distill.00003","volume":"1","author":"A Odena","year":"2016","unstructured":"Odena, A., Dumoulin, V., Olah, C.: Deconvolution and checkerboard artifacts. Distill 1(10), e3 (2016)","journal-title":"Distill"},{"issue":"1","key":"17_CR10","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/s10255-007-7006-9","volume":"24","author":"GR Qu","year":"2008","unstructured":"Qu, G.R., Lan, Y.S., Jiang, M.: An iterative algorithm for angle-limited three-dimensional image reconstruction. Acta Math. Appl. Sin. Engl. Ser. 24(1), 157\u2013166 (2008)","journal-title":"Acta Math. Appl. Sin. Engl. Ser."},{"key":"17_CR11","unstructured":"Riess, C., Berger, M., Wu, H., Manhart, M., Fahrig, R., Maier, A.: TV or not TV? That is the question. In: Proceedings of Fully3D, pp. 341\u2013344 (2013)"},{"key":"17_CR12","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. LNCS, vol. 9351, pp. 234\u2013241. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-24574-4_28"},{"issue":"17","key":"17_CR13","doi-asserted-by":"publisher","first-page":"4777","DOI":"10.1088\/0031-9155\/53\/17\/021","volume":"53","author":"E Sidky","year":"2008","unstructured":"Sidky, E., Pan, X.: Image reconstruction in circular cone-beam computed tomography by constrained, total-variation minimization. Phys. Med. Biol. 53(17), 4777\u20134807 (2008)","journal-title":"Phys. Med. Biol."},{"key":"17_CR14","unstructured":"Szegedy, C., et al.: Intriguing properties of neural networks. arXiv preprint (2013)"},{"issue":"6","key":"17_CR15","doi-asserted-by":"publisher","first-page":"1454","DOI":"10.1109\/TMI.2018.2833499","volume":"37","author":"T W\u00fcrfl","year":"2018","unstructured":"W\u00fcrfl, T., et al.: Deep learning computed tomography: learning projection-domain weights from image domain in limited angle problems. IEEE Trans. Med. Imaging 37(6), 1454\u20131463 (2018)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"17_CR16","unstructured":"Yuan, X., He, P., Zhu, Q., Bhat, R.R., Li, X.: Adversarial examples: attacks and defenses for deep learning. arXiv preprint (2017)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-00928-1_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T00:37:12Z","timestamp":1694565432000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-00928-1_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030009274","9783030009281"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-00928-1_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"26 September 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Granada","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}