{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,30]],"date-time":"2025-04-30T04:13:45Z","timestamp":1745986425745,"version":"3.40.4"},"publisher-location":"Cham","reference-count":9,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031832734"},{"type":"electronic","value":"9783031832741"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,3,3]],"date-time":"2025-03-03T00:00:00Z","timestamp":1740960000000},"content-version":"vor","delay-in-days":61,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>The segmentation of head and neck cancer (HNC) tumors is a critical step in radiotherapy treatment planning. The development of automatic segmentation algorithms has the potential to streamline the radiation oncology process. In this work, we develop an ensemble of LinkNet networks for HNC tumor segmentation as part of the HNTS-MRG 2024 Grand Challenge. A single LinkNet network, pretrained on the Imagenet dataset, was trained for 200 epochs on the HNC dataset provided by the challenge. Eight good performing weights from the internal validation set were selected to create an ensemble of 2D networks. Specifically, each selected weight was used to generate a LinkNet architecture, resulting in eight networks whose predictions were averaged to produce the final predicted segmentation. Our experiments demonstrate that the ensemble network performs better than each individual architecture, leveraging the benefits of ensemble learning without the computational cost of training each network from scratch. In the challenge\u2019s test set, the LinkNet Ensemble (team ECU) achieved an aggregated Dice score of 64.60% and 49.53% for metastatic lymph nodes and primary gross tumor segmentation, respectively, and a mean score of 57.06%.<\/jats:p>","DOI":"10.1007\/978-3-031-83274-1_16","type":"book-chapter","created":{"date-parts":[[2025,3,2]],"date-time":"2025-03-02T12:42:37Z","timestamp":1740919357000},"page":"214-221","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Ensemble of\u00a0LinkNet Networks for\u00a0Head and\u00a0Neck Tumor Segmentation"],"prefix":"10.1007","author":[{"given":"Maria","family":"Baldeon-Calisto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,3,3]]},"reference":[{"issue":"10318","key":"16_CR1","doi-asserted-by":"publisher","first-page":"2289","DOI":"10.1016\/S0140-6736(21)01550-6","volume":"398","author":"MD Mody","year":"2021","unstructured":"Mody, M.D., Rocco, J.W., Yom, S.S., Haddad, R.I., Saba, N.F.: Head and neck cancer. The Lancet 398(10318), 2289\u20132299 (2021)","journal-title":"The Lancet"},{"key":"16_CR2","doi-asserted-by":"publisher","first-page":"1020","DOI":"10.3389\/fonc.2020.01020","volume":"10","author":"H Konings","year":"2020","unstructured":"Konings, H., et al.: A literature review of the potential diagnostic biomarkers of head and neck neoplasms. Front. Oncol. 10, 1020 (2020)","journal-title":"Front. Oncol."},{"key":"16_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12901-018-0061-4","volume":"18","author":"MR Gore","year":"2018","unstructured":"Gore, M.R.: Survival in sinonasal and middle ear malignancies: a population-based study using the seer 1973\u20132015 database. BMC Ear Nose Throat Disord. 18, 1\u201311 (2018)","journal-title":"BMC Ear Nose Throat Disord."},{"issue":"10","key":"16_CR4","doi-asserted-by":"publisher","first-page":"4558","DOI":"10.1002\/mp.13147","volume":"45","author":"N Tong","year":"2018","unstructured":"Tong, N., Gou, S., Yang, S., Ruan, D., Sheng, K.: Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks. Med. Phys. 45(10), 4558\u20134567 (2018)","journal-title":"Med. Phys."},{"key":"16_CR5","unstructured":"Nikolov, S., et\u00a0al.: Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy. arXiv preprint arXiv:1809.04430 (2018)"},{"issue":"9","key":"16_CR6","doi-asserted-by":"publisher","first-page":"5310","DOI":"10.1118\/1.4928485","volume":"42","author":"J Yang","year":"2015","unstructured":"Yang, J., Beadle, B.M., Garden, A.S., Schwartz, D.L., Aristophanous, M.: A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy. Med. Phys. 42(9), 5310\u20135320 (2015)","journal-title":"Med. Phys."},{"key":"16_CR7","doi-asserted-by":"crossref","unstructured":"Chaurasia, A., Culurciello, E.: Linknet: exploiting encoder representations for efficient semantic segmentation. In: 2017 IEEE Visual Communications and Image Processing (VCIP), pp.\u00a01\u20134. IEEE (2017)","DOI":"10.1109\/VCIP.2017.8305148"},{"key":"16_CR8","doi-asserted-by":"crossref","unstructured":"Ara\u00fajo, R.L., Ara\u00fajo, F.H.D., Silva, R.R.E.: Automatic segmentation of melanoma skin cancer using transfer learning and fine-tuning. Multimedia Syst. 28(4), 1239\u20131250 (2022)","DOI":"10.1007\/s00530-021-00840-3"},{"key":"16_CR9","doi-asserted-by":"crossref","unstructured":"Granizo, S., et al.: A comparative analysis of vision transformers and convolutional neural networks in cardiac image segmentation. In: 2024 12th International Symposium on Digital Forensics and Security (ISDFS), pp.\u00a01\u20137. IEEE (2024)","DOI":"10.1109\/ISDFS60797.2024.10527254"}],"container-title":["Lecture Notes in Computer Science","Head and Neck Tumor Segmentation for MR-Guided Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-83274-1_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,29]],"date-time":"2025-04-29T10:45:24Z","timestamp":1745923524000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-83274-1_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031832734","9783031832741"],"references-count":9,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-83274-1_16","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"3 March 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HNTSMRG","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Challenge on Head and Neck Tumor Segmentation for MRI-Guided Applications","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":"9 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hntsmrg2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/hntsmrg24.grand-challenge.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}