{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T17:30:20Z","timestamp":1770226220134,"version":"3.49.0"},"publisher-location":"Cham","reference-count":13,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030609450","type":"print"},{"value":"9783030609467","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-60946-7_10","type":"book-chapter","created":{"date-parts":[[2020,10,3]],"date-time":"2020-10-03T16:02:29Z","timestamp":1601740949000},"page":"97-105","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Soft Tissue Sarcoma Co-segmentation in Combined MRI and PET\/CT Data"],"prefix":"10.1007","author":[{"given":"Theresa","family":"Neubauer","sequence":"first","affiliation":[]},{"given":"Maria","family":"Wimmer","sequence":"additional","affiliation":[]},{"given":"Astrid","family":"Berg","sequence":"additional","affiliation":[]},{"given":"David","family":"Major","sequence":"additional","affiliation":[]},{"given":"Dimitrios","family":"Lenis","sequence":"additional","affiliation":[]},{"given":"Thomas","family":"Beyer","sequence":"additional","affiliation":[]},{"given":"Jelena","family":"Saponjski","sequence":"additional","affiliation":[]},{"given":"Katja","family":"B\u00fchler","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,10,1]]},"reference":[{"issue":"6","key":"10_CR1","doi-asserted-by":"publisher","first-page":"1045","DOI":"10.1007\/s10278-013-9622-7","volume":"26","author":"K Clark","year":"2013","unstructured":"Clark, K., et al.: The cancer imaging archive (TCIA): maintaining and operating a public information repository. J. Digit. Imaging 26(6), 1045\u20131057 (2013). https:\/\/doi.org\/10.1007\/s10278-013-9622-7","journal-title":"J. Digit. Imaging"},{"key":"10_CR2","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE CVPR, pp. 4700\u20134708. IEEE (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"10_CR3","doi-asserted-by":"publisher","unstructured":"Isensee, F., Kickingereder, P., Wick, W., Bendszus, M., Maier-Hein, K.H.: No new-net. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) BrainLes 2018. LNCS, vol. 11384, pp. 234\u2013244. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11726-9_21","DOI":"10.1007\/978-3-030-11726-9_21"},{"key":"10_CR4","doi-asserted-by":"crossref","unstructured":"J\u00e9gou, S., Drozdzal, M., Vazquez, D., Romero, A., Bengio, Y.: The one hundred layers tiramisu: fully convolutional DenseNets for semantic segmentation. In: Proceedings of the IEEE CVPR Workshops, pp. 11\u201319. IEEE (2017)","DOI":"10.1109\/CVPRW.2017.156"},{"issue":"1","key":"10_CR5","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1109\/TMI.2019.2923601","volume":"39","author":"A Kumar","year":"2020","unstructured":"Kumar, A., Fulham, M., Feng, D., Kim, J.: Co-learning feature fusion maps from PET-CT images of lung cancer. IEEE Trans. Med. Imaging 39(1), 204\u2013217 (2020)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"7","key":"10_CR6","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.3109\/0284186X.2013.813964","volume":"52","author":"S Leibfarth","year":"2013","unstructured":"Leibfarth, S., et al.: A strategy for multimodal deformable image registration to integrate PET\/MR into radiotherapy treatment planning. Acta Oncologica 52(7), 1353\u20131359 (2013)","journal-title":"Acta Oncologica"},{"key":"10_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1007\/978-3-030-11726-9_28","volume-title":"Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries","author":"A Myronenko","year":"2019","unstructured":"Myronenko, A.: 3D MRI brain tumor segmentation using autoencoder regularization. In: Crimi, A., Bakas, S., Kuijf, H., Keyvan, F., Reyes, M., van Walsum, T. (eds.) BrainLes 2018. LNCS, vol. 11384, pp. 311\u2013320. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-11726-9_28"},{"key":"10_CR8","unstructured":"Ramachandran, P., Zoph, B., Le, Q.V.: Searching for activation functions. arXiv preprint arXiv:1710.05941 (2017)"},{"key":"10_CR9","doi-asserted-by":"publisher","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","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"10_CR10","doi-asserted-by":"publisher","DOI":"10.7937\/K9\/TCIA.2015.7GO2GSKS","author":"M Valli\u00e8res","year":"2015","unstructured":"Valli\u00e8res, M., Freeman, C.R., Skamene, S.R., El Naqa, I.: A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities. Cancer Imaging Arch. (2015). https:\/\/doi.org\/10.7937\/K9\/TCIA.2015.7GO2GSKS","journal-title":"Cancer Imaging Arch."},{"issue":"14","key":"10_CR11","doi-asserted-by":"publisher","first-page":"5471","DOI":"10.1088\/0031-9155\/60\/14\/5471","volume":"60","author":"M Valli\u00e8res","year":"2015","unstructured":"Valli\u00e8res, M., Freeman, C.R., Skamene, S.R., El Naqa, I.: A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities. Phys. Med. Biol. 60(14), 5471\u20135496 (2015)","journal-title":"Phys. Med. Biol."},{"issue":"2","key":"10_CR12","doi-asserted-by":"publisher","first-page":"619","DOI":"10.1002\/mp.13331","volume":"46","author":"Z Zhong","year":"2019","unstructured":"Zhong, Z., et al.: Simultaneous cosegmentation of tumors in PET-CT images using deep fully convolutional networks. Med. Phys. 46(2), 619\u2013633 (2019)","journal-title":"Med. Phys."},{"issue":"10004","key":"10_CR13","first-page":"1","volume":"3\u20134","author":"T Zhou","year":"2019","unstructured":"Zhou, T., Ruan, S., Canu, S.: A review: deep learning for medical image segmentation using multi-modality fusion. Array 3\u20134(10004), 1\u201311 (2019)","journal-title":"Array"}],"container-title":["Lecture Notes in Computer Science","Multimodal Learning for Clinical Decision Support and Clinical Image-Based Procedures"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-60946-7_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,2]],"date-time":"2025-10-02T22:04:12Z","timestamp":1759442652000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-60946-7_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030609450","9783030609467"],"references-count":13,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-60946-7_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"1 October 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ML-CDS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Multimodal Learning for Clinical Decision Support","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lima","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Peru","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 October 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ml-cds2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/mcbr-cds.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}