{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T00:46:14Z","timestamp":1760229974192,"version":"build-2065373602"},"reference-count":67,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T00:00:00Z","timestamp":1656979200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the National Natural Science Foundation of China","award":["61901533","62101610","JCYJ20190807154601663","2021M693673"],"award-info":[{"award-number":["61901533","62101610","JCYJ20190807154601663","2021M693673"]}]},{"name":"the Shenzhen Fundamental Research Program, China","award":["61901533","62101610","JCYJ20190807154601663","2021M693673"],"award-info":[{"award-number":["61901533","62101610","JCYJ20190807154601663","2021M693673"]}]},{"DOI":"10.13039\/501100002858","name":"the China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["61901533","62101610","JCYJ20190807154601663","2021M693673"],"award-info":[{"award-number":["61901533","62101610","JCYJ20190807154601663","2021M693673"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Accurate segmentation of nasopharyngeal carcinoma is essential to its treatment effect. However, there are several challenges in existing deep learning-based segmentation methods. First, the acquisition of labeled data are challenging. Second, the nasopharyngeal carcinoma is similar to the surrounding tissues. Third, the shape of nasopharyngeal carcinoma is complex. These challenges make the segmentation of nasopharyngeal carcinoma difficult. This paper proposes a novel semi-supervised method named CAFS for automatic segmentation of nasopharyngeal carcinoma. CAFS addresses the above challenges through three mechanisms: the teacher\u2013student cooperative segmentation mechanism, the attention mechanism, and the feedback mechanism. CAFS can use only a small amount of labeled nasopharyngeal carcinoma data to segment the cancer region accurately. The average DSC value of CAFS is 0.8723 on the nasopharyngeal carcinoma segmentation task. Moreover, CAFS has outperformed the state-of-the-art nasopharyngeal carcinoma segmentation methods in the comparison experiment. Among the compared state-of-the-art methods, CAFS achieved the highest values of DSC, Jaccard, and precision. In particular, the DSC value of CAFS is 7.42% higher than the highest DSC value in the state-of-the-art methods.<\/jats:p>","DOI":"10.3390\/s22135053","type":"journal-article","created":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T21:15:52Z","timestamp":1657142152000},"page":"5053","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["CAFS: An Attention-Based Co-Segmentation Semi-Supervised Method for Nasopharyngeal Carcinoma Segmentation"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3306-097X","authenticated-orcid":false,"given":"Yitong","family":"Chen","sequence":"first","affiliation":[{"name":"School of Biomedical Engineering, Sun Yat-sen University, Shenzhen 518107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9043-722X","authenticated-orcid":false,"given":"Guanghui","family":"Han","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Sun Yat-sen University, Shenzhen 518107, China"},{"name":"School of Information Engineering, North China University of Water Resources and Electric Power, Zhengzhou 450046, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4202-4970","authenticated-orcid":false,"given":"Tianyu","family":"Lin","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Sun Yat-sen University, Shenzhen 518107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6198-2453","authenticated-orcid":false,"given":"Xiujian","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Sun Yat-sen University, Shenzhen 518107, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/j.jocs.2017.03.021","article-title":"Review on Nasopharyngeal Carcinoma: Concepts, methods of analysis, segmentation, classification, prediction and impact: A review of the research literature","volume":"21","author":"Mohammed","year":"2017","journal-title":"J. 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