{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:20:25Z","timestamp":1773246025582,"version":"3.50.1"},"publisher-location":"Cham","reference-count":39,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031721038","type":"print"},{"value":"9783031721045","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-72104-5_28","type":"book-chapter","created":{"date-parts":[[2024,10,2]],"date-time":"2024-10-02T12:02:53Z","timestamp":1727870573000},"page":"285-295","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["EchoNet-Synthetic: Privacy-Preserving Video Generation for\u00a0Safe Medical Data Sharing"],"prefix":"10.1007","author":[{"given":"Hadrien","family":"Reynaud","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingjie","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mischa","family":"Dombrowski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Arijit","family":"Ghosh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Thomas","family":"Day","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alberto","family":"Gomez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul","family":"Leeson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bernhard","family":"Kainz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,3]]},"reference":[{"key":"28_CR1","unstructured":"An, J., Zhang, S., Yang, H., Gupta, S., Huang, J.B., et\u00a0al.: Latent-shift: latent diffusion with temporal shift for efficient text-to-video generation. arXiv preprint arXiv:2304.08477 (2023)"},{"key":"28_CR2","unstructured":"Blattmann, A., et\u00a0al.: Stable video diffusion: scaling latent video diffusion models to large datasets. arXiv preprint arXiv:2311.15127 (2023)"},{"key":"28_CR3","doi-asserted-by":"crossref","unstructured":"Blattmann, A., Rombach, R., Ling, H., Dockhorn, T., Kim, S.W., et\u00a0al.: Align your latents: high-resolution video synthesis with latent diffusion models. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 22563\u201322575 (2023)","DOI":"10.1109\/CVPR52729.2023.02161"},{"key":"28_CR4","unstructured":"Bommasani, R., et\u00a0al.: On the opportunities and risks of foundation models. arXiv preprint arXiv:2108.07258 (2021)"},{"key":"28_CR5","unstructured":"Carlini, N., et al.: Extracting training data from diffusion models. In: 32nd USENIX Security Symposium (USENIX Security 2023), pp. 5253\u20135270 (2023)"},{"key":"28_CR6","unstructured":"Dar, S.U.H., et al.: Unconditional latent diffusion models memorize patient imaging data. arXiv preprint arXiv:2402.01054 (2024)"},{"key":"28_CR7","unstructured":"Dombrowski, M., Kainz, B.: Quantifying sample anonymity in score-based generative models with adversarial fingerprinting (2023)"},{"issue":"10","key":"28_CR8","doi-asserted-by":"publisher","first-page":"2783","DOI":"10.1109\/TMI.2021.3051806","volume":"40","author":"A Gilbert","year":"2021","unstructured":"Gilbert, A., Marciniak, M., Rodero, C., Lamata, P., Samset, E., Mcleod, K.: Generating synthetic labeled data from existing anatomical models: an example with echocardiography segmentation. IEEE Trans. Med. Imaging 40(10), 2783\u20132794 (2021)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"28_CR9","unstructured":"Goodfellow, I., et al.: Generative adversarial nets. Adv. Neural Inf. Process. Syst. 27 (2014)"},{"key":"28_CR10","unstructured":"Harvey, W., Naderiparizi, S., Masrani, V., Weilbach, C., Wood, F.: Flexible diffusion modeling of long videos. arXiv:2205.11495 (2022)"},{"key":"28_CR11","unstructured":"He, Y., Yang, T., Zhang, Y., Shan, Y., Chen, Q.: Latent video diffusion models for high-fidelity video generation with arbitrary lengths. arXiv preprint arXiv:2211.13221 (2022)"},{"key":"28_CR12","unstructured":"Ho, J., Chan, W., Saharia, C., Whang, J., Gao, R., et\u00a0al.: Imagen video: high definition video generation with diffusion models. arXiv:2210.02303 (2022)"},{"key":"28_CR13","unstructured":"Ho, J., Jain, A., Abbeel, P.: Denoising Diffusion Probabilistic Models. In: Advances in Neural Information Processing Systems, vol.\u00a033, pp. 6840\u20136851 (2020)"},{"key":"28_CR14","unstructured":"Ho, J., Salimans, T., Gritsenko, A., Chan, W., Norouzi, M., et\u00a0al.: Video diffusion models. arXiv:2204.03458 (2022)"},{"key":"28_CR15","unstructured":"Hoeppe, T., Mehrjou, A., Bauer, S., Nielsen, D., Dittadi, A.: Diffusion models for video prediction and infilling. arXiv preprint arXiv:2206.07696 (2022)"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Jensen, J.: Simulation of advanced ultrasound systems using field II. In: 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821), vol. 1, pp. 636\u2013639 (2004)","DOI":"10.1109\/ISBI.2004.1398618"},{"key":"28_CR17","doi-asserted-by":"crossref","unstructured":"Khachatryan, L., Movsisyan, A., Tadevosyan, V., Henschel, R., Wang, Z., et\u00a0al.: Text2video-zero: Text-to-image diffusion models are zero-shot video generators. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV) (2023)","DOI":"10.1109\/ICCV51070.2023.01462"},{"key":"28_CR18","doi-asserted-by":"publisher","first-page":"102461","DOI":"10.1016\/j.media.2022.102461","volume":"79","author":"J Liang","year":"2022","unstructured":"Liang, J., Yang, X., Huang, Y., Li, H., He, S., et al.: Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis. Med. Image Anal. 79, 102461 (2022)","journal-title":"Med. Image Anal."},{"key":"28_CR19","doi-asserted-by":"crossref","unstructured":"Luo, Z., Chen, D., Zhang, Y., Huang, Y., Wang, L., et\u00a0al.: VideoFusion: decomposed diffusion models for high-quality video generation. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.10308948"},{"key":"28_CR20","unstructured":"Nikankin, Y., Haim, N., Irani, M.: SinFusion: training diffusion models on a single image or video. arXiv preprint arXiv:2211.11743 (2022)"},{"key":"28_CR21","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1038\/s41586-020-2145-8","volume":"580","author":"D Ouyang","year":"2020","unstructured":"Ouyang, D., He, B., Ghorbani, A., Yuan, N., Ebinger, J., et al.: Video-based AI for beat-to-beat assessment of cardiac function. Nature 580, 252\u2013256 (2020)","journal-title":"Nature"},{"issue":"1","key":"28_CR22","doi-asserted-by":"publisher","first-page":"14851","DOI":"10.1038\/s41598-022-19045-3","volume":"12","author":"K Packh\u00e4user","year":"2022","unstructured":"Packh\u00e4user, K., G\u00fcndel, S., M\u00fcnster, N., Syben, C., Christlein, V., Maier, A.: Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest X-ray data. Sci. Rep. 12(1), 14851 (2022)","journal-title":"Sci. Rep."},{"issue":"5","key":"28_CR23","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.echo.2023.01.015","volume":"36","author":"CD Reddy","year":"2023","unstructured":"Reddy, C.D., Lopez, L., Ouyang, D., Zou, J.Y., He, B.: Video-based deep learning for automated assessment of left ventricular ejection fraction in pediatric patients. J. Am. Soc. Echocardiogr. 36(5), 482\u2013489 (2023)","journal-title":"J. Am. Soc. Echocardiogr."},{"key":"28_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1007\/978-3-031-43999-5_14","volume-title":"Medical Image Computing and Computer Assisted Intervention - MICCAI 2023","author":"H Reynaud","year":"2023","unstructured":"Reynaud, H., et al.: Feature-conditioned cascaded video diffusion models for precise echocardiogram synthesis. In: Greenspan, H., et al. (eds.) MICCAI 2023. LNCS, vol. 14229, pp. 142\u2013152. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-43999-5_14"},{"key":"28_CR25","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1007\/978-3-031-16452-1_57","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022","author":"H Reynaud","year":"2022","unstructured":"Reynaud, H., Vlontzos, A., Dombrowski, M., Gilligan Lee, C., Beqiri, A., et al.: D\u2019ARTAGNAN: counterfactual video generation. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds.) MICCAI 2022. LNCS, vol. 13438, pp. 599\u2013609. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16452-1_57"},{"key":"28_CR26","doi-asserted-by":"crossref","unstructured":"Rombach, R., Blattmann, A., Lorenz, D., Esser, P., Ommer, B.: High-resolution image synthesis with latent diffusion models. arXiv:2112.10752 (2022)","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"28_CR27","doi-asserted-by":"crossref","unstructured":"Rueckert, D., Glocker, B., Kainz, B.: Learning clinically useful information from images: past, present and future (2016)","DOI":"10.1016\/j.media.2016.06.009"},{"key":"28_CR28","unstructured":"Salimans, T., Ho, J.: Progressive distillation for fast sampling of diffusion models. arXiv:2202.00512 (2022)"},{"key":"28_CR29","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1007\/978-3-540-85990-1_88","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2008","author":"R Shams","year":"2008","unstructured":"Shams, R., Hartley, R., Navab, N.: Real-time simulation of medical ultrasound from CT images. In: Metaxas, D., Axel, L., Fichtinger, G., Sz\u00e9kely, G. (eds.) MICCAI 2008. LNCS, vol. 5242, pp. 734\u2013741. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-85990-1_88"},{"key":"28_CR30","unstructured":"Singer, U., Polyak, A., Hayes, T., Yin, X., An, J., et\u00a0al.: Make-a-video: text-to-video generation without text-video data. arXiv:2209.14792 (2022)"},{"key":"28_CR31","doi-asserted-by":"publisher","first-page":"106147","DOI":"10.1109\/ACCESS.2020.3000666","volume":"8","author":"L Teng","year":"2020","unstructured":"Teng, L., Fu, Z., Yao, Y.: Interactive translation in echocardiography training system with enhanced cycle-GAN. IEEE Access 8, 106147\u2013106156 (2020)","journal-title":"IEEE Access"},{"key":"28_CR32","doi-asserted-by":"publisher","first-page":"98803","DOI":"10.1109\/ACCESS.2022.3207177","volume":"10","author":"C Tiago","year":"2022","unstructured":"Tiago, C., et al.: A data augmentation pipeline to generate synthetic labeled datasets of 3D echocardiography images using a GAN. IEEE Access 10, 98803\u201398815 (2022)","journal-title":"IEEE Access"},{"key":"28_CR33","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1007\/978-3-030-87237-3_63","volume-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","author":"D Tomar","year":"2021","unstructured":"Tomar, D., Zhang, L., Portenier, T., Goksel, O.: Content-preserving unpaired translation from simulated to realistic ultrasound images. In: de Bruijne, M., et al. (eds.) MICCAI 2021. LNCS, vol. 12908, pp. 659\u2013669. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87237-3_63"},{"key":"28_CR34","unstructured":"Voleti, V., Jolicoeur-Martineau, A., Pal, C.: Masked conditional video diffusion for prediction, generation, and interpolation. arXiv preprint arXiv:2205.09853 (2022)"},{"key":"28_CR35","unstructured":"Wang, W., Yang, H., Tuo, Z., He, H., Zhu, J., et\u00a0al.: VideoFactory: swap attention in spatiotemporal diffusions for text-to-video generation. arXiv preprint arXiv:2305.10874 (2023)"},{"key":"28_CR36","doi-asserted-by":"crossref","unstructured":"Yang, R., Srivastava, P., Mandt, S.: Diffusion probabilistic modeling for video generation. arXiv:2203.09481 (2022)","DOI":"10.3390\/e25101469"},{"key":"28_CR37","doi-asserted-by":"crossref","unstructured":"Yu, S., Sohn, K., Kim, S., Shin, J.: Video probabilistic diffusion models in projected latent space. In: CVPR (2023)","DOI":"10.1109\/CVPR52729.2023.01770"},{"key":"28_CR38","doi-asserted-by":"crossref","unstructured":"Zhang, R., Isola, P., Efros, A.A., Shechtman, E., Wang, O.: The unreasonable effectiveness of deep features as a perceptual metric. In: CVPR (2018)","DOI":"10.1109\/CVPR.2018.00068"},{"key":"28_CR39","unstructured":"Zhou, D., Wang, W., Yan, H., Lv, W., Zhu, Y., et\u00a0al.: MagicVideo: efficient video generation with latent diffusion models. arXiv preprint arXiv:2211.11018 (2022)"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72104-5_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,7]],"date-time":"2024-12-07T09:07:16Z","timestamp":1733562436000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72104-5_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031721038","9783031721045"],"references-count":39,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72104-5_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 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 are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"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":"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":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}