{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:10:30Z","timestamp":1763338230652,"version":"3.40.3"},"publisher-location":"Cham","reference-count":24,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031765834"},{"type":"electronic","value":"9783031765841"}],"license":[{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,11,3]],"date-time":"2024-11-03T00:00:00Z","timestamp":1730592000000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-76584-1_10","type":"book-chapter","created":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T17:02:38Z","timestamp":1730566958000},"page":"114-126","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Comparison of Architectures of Deep Learning-Based Segmentation in Lower Extremity Human Thermal Imaging"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9512-5494","authenticated-orcid":false,"given":"Mete Can","family":"Ya\u015far","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-8630-9564","authenticated-orcid":false,"given":"Mahmut","family":"\u00c7evik","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6898-7083","authenticated-orcid":false,"given":"\u015eeyda","family":"Besnili","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6503-9668","authenticated-orcid":false,"given":"Murat","family":"Ceylan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,11,3]]},"reference":[{"key":"10_CR1","doi-asserted-by":"crossref","unstructured":"Qal\u0131, A., Selek, M.: Diz Osteoartritinde Tan\u0131 \u0130\u00e7in Termal G\u00f6r\u00fcnt\u00fc \u0130\u015flemenin Uygulanmas\u0131. Avrupa Bilim ve Teknoloji Dergisi (2020)","DOI":"10.31590\/ejosat.802936"},{"issue":"1","key":"10_CR2","first-page":"12","volume":"3","author":"B Demir","year":"2024","unstructured":"Demir, B., \u0130l\u00e7e, A.: K\u0131z\u0131l\u00f6tesi Termal Kameran\u0131n Sa\u011fl\u0131k Alanlar\u0131nda Kullan\u0131m\u0131. Sa\u011fl\u0131k Bak\u0131m ve Rehabilitasyon Dergisi 3(1), 12\u201325 (2024)","journal-title":"Sa\u011fl\u0131k Bak\u0131m ve Rehabilitasyon Dergisi"},{"key":"10_CR3","first-page":"109","volume":"98","author":"T Kernbauer","year":"2024","unstructured":"Kernbauer, T., Fleck, P., Arth, C.: PanoTherm: panoramic thermal imaging for object detection and tracking. Proc. Copyright 98, 109 (2024)","journal-title":"Proc. Copyright"},{"key":"10_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.infrared.2024.105285","volume":"139","author":"J Pi","year":"2024","unstructured":"Pi, J., Wen, F., Lu, Q., Jiang, N., Wu, H., Liu, Q.: Digital thermal infrared detector attack via free velocity and rollback mutation. Infrared Phys. Technol. 139, 105285 (2024)","journal-title":"Infrared Phys. Technol."},{"key":"10_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.122275","volume":"239","author":"LJ Gruber","year":"2024","unstructured":"Gruber, L.J., et al.: Accuracy and precision of mandible segmentation and its clinical implications: virtual reality, desktop screen and artificial intelligence. Expert Syst. Appl. 239, 122275 (2024)","journal-title":"Expert Syst. Appl."},{"key":"10_CR6","doi-asserted-by":"crossref","unstructured":"Ehrenfeuchter, S., Corlito, R., Marchthaler, R., Enzweiler, M.: Real-time semantic segmentation for autonomous scale cars using mixed real and synthetic data. In: 2024 10th International Conference on Mechatronics and Robotics Engineering (ICMRE), 27\u201329 Feb 2024, pp. 86\u201391 (2024)","DOI":"10.1109\/ICMRE60776.2024.10532162"},{"key":"10_CR7","doi-asserted-by":"crossref","unstructured":"K\u00fct\u00fck, Z., Algan, G.: Semantic segmentation for thermal images: a comparative survey. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 286\u2013295 (2022)","DOI":"10.1109\/CVPRW56347.2022.00043"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Hou, Y.-Y.: Applications of \u0131mage segmentation techniques in medical \u0131mages. EAI Endorsed Trans. e-Learn. 10 (2024)","DOI":"10.4108\/eetel.4449"},{"key":"10_CR9","doi-asserted-by":"crossref","unstructured":"Arsen, P., Skublewska-Paszkowska, M., Powro\u017anik, P.: A comparative analysis of image segmentation using classical and deep learning approach.\u00a0Adv. Sci. Technol. Res. J.\u00a017.6 (2023).","DOI":"10.12913\/22998624\/172771"},{"key":"10_CR10","doi-asserted-by":"crossref","unstructured":"Guan, S., Kamona, N., Loew, M.: Segmentation of thermal breast images using convolutional and deconvolutional neural networks. In: 2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pp. 1\u20137. IEEE (2018)","DOI":"10.1109\/AIPR.2018.8707379"},{"issue":"3","key":"10_CR11","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1080\/17686733.2020.1720344","volume":"18","author":"M Mazur-Milecka","year":"2021","unstructured":"Mazur-Milecka, M., Ruminski, J.: Deep learning based thermal image segmentation for laboratory animals tracking. Quant. InfraRed Thermography J. 18(3), 159\u2013176 (2021)","journal-title":"Quant. InfraRed Thermography J."},{"key":"10_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2020.103085","volume":"202","author":"A Pemasiri","year":"2021","unstructured":"Pemasiri, A., Nguyen, K., Sridharan, S., Fookes, C.: Multi-modal semantic image segmentation. Comput. Vis. Image Understand. 202, 103085 (2021)","journal-title":"Comput. Vis. Image Understand."},{"key":"10_CR13","doi-asserted-by":"crossref","unstructured":"Voss, F., Brechmann, N., Lyra, S., Rixen, J., Leonhardt, S., Hoog Antink, C.: Multi-modal body part segmentation of infants using deep learning. BioMed. Eng. OnLine 22(1), 28 (2023)","DOI":"10.1186\/s12938-023-01092-0"},{"issue":"3","key":"10_CR14","volume":"17","author":"W Xiao","year":"2024","unstructured":"Xiao, W., Lyu, Y.: Human computer interaction product for infrared thermographic fundus retinal vessels image segmentation using U-Net. J. Radiat. Res. Appl. Sci. 17(3), 101003 (2024)","journal-title":"J. Radiat. Res. Appl. Sci."},{"key":"10_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108209","volume":"251","author":"M Etehadtavakol","year":"2024","unstructured":"Etehadtavakol, M., Etehadtavakol, M., Ng, E.Y.K.: Enhanced thyroid nodule segmentation through U-Net and VGG16 fusion with feature engineering: a comprehensive study. Comput. Meth. Program. Biomed. 251, 108209 (2024)","journal-title":"Comput. Meth. Program. Biomed."},{"key":"10_CR16","unstructured":"ai4sports aivisiontech (2018). www.aivisiontech.net"},{"key":"10_CR17","doi-asserted-by":"publisher","unstructured":"Ergene, M.C., et al.: Evaluation of deep learning models for lower extremity muscle segmentation in thermal imaging. In: Kakileti, S.T., Manjunath, G., Schwartz, R.G., Frangi, A.F. (eds.) Artificial Intelligence over Infrared Images for Medical Applications. AIIIMA 2023. LNCS, vol. 14298. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-44511-8_9","DOI":"10.1007\/978-3-031-44511-8_9"},{"key":"10_CR18","first-page":"234","volume-title":"Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference, Munich, Germany, October 5\u20139, 2015, Proceedings, Part III 18","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger, O., Fischer, P., Brox, T.: U-net: convolutional networks for biomedical image segmentation. In: Medical Image Computing and Computer-Assisted Intervention\u2013MICCAI 2015: 18th International Conference, Munich, Germany, October 5\u20139, 2015, Proceedings, Part III 18, pp. 234\u2013241. Springer (2015)"},{"key":"10_CR19","unstructured":"Oktay, O., et al.: Attention U-Net: learning where to look for the pancreas. arXiv preprint arXiv:1804.03999, 2018."},{"key":"10_CR20","doi-asserted-by":"crossref","unstructured":"Alom, M.Z., Hasan, M., Yakopcic, C., Taha, T.M., Asari, V.K.: Recurrent residual convolutional neural network based on U-Net (R2U-Net) for medical \u0131mage segmentation. arXiv preprint arXiv:1802.06955 (2018)","DOI":"10.1109\/NAECON.2018.8556686"},{"key":"10_CR21","doi-asserted-by":"crossref","unstructured":"Zuo, Q., Chen, S., Wang, Z.: R2AU-Net: attention recurrent residual convolutional neural network for multimodal medical \u0131mage segmentation. Secur. Commun. Networks 2021, 6625688:1\u20136625688:10 (2021)","DOI":"10.1155\/2021\/6625688"},{"issue":"10","key":"10_CR22","doi-asserted-by":"publisher","first-page":"3349","DOI":"10.1109\/TPAMI.2020.2983686","volume":"43","author":"J Wang","year":"2020","unstructured":"Wang, J., et al.: Deep high-resolution representation learning for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 43(10), 3349\u20133364 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10_CR23","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1016\/j.neucom.2021.10.102","volume":"470","author":"M Lou","year":"2022","unstructured":"Lou, M., Meng, J., Qi, Y., Li, X., Ma, Y.: MCRNet: multi-level context refinement network for semantic segmentation in breast ultrasound imaging. Neurocomputing 470, 154\u2013169 (2022)","journal-title":"Neurocomputing"},{"key":"10_CR24","unstructured":"Vaswani, A., et al.: Attention is all you need. Neural Information Processing Systems (NeurIPS) (2017)"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence over Infrared Images for Medical Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-76584-1_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,2]],"date-time":"2024-11-02T17:03:18Z","timestamp":1730566998000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-76584-1_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,11,3]]},"ISBN":["9783031765834","9783031765841"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-76584-1_10","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,11,3]]},"assertion":[{"value":"3 November 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIIIMA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"MICCAI Workshop on Artificial Intelligence over Infrared Images for Medical Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 November 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 November 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aiiima2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/sites.google.com\/niramai.com\/aiiima","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}