{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,11]],"date-time":"2024-08-11T05:12:33Z","timestamp":1723353153272},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T00:00:00Z","timestamp":1643414400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T00:00:00Z","timestamp":1643414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100004663","name":"Ministry of Science and Technology, Taiwan","doi-asserted-by":"publisher","award":["108-2221-E-194 -042"],"id":[{"id":"10.13039\/501100004663","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,4]]},"DOI":"10.1007\/s11042-021-11889-7","type":"journal-article","created":{"date-parts":[[2022,1,29]],"date-time":"2022-01-29T18:02:36Z","timestamp":1643479356000},"page":"11881-11895","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A multiple organ segmentation system for CT image series using Attention-LSTM fused U-Net"],"prefix":"10.1007","volume":"81","author":[{"given":"Pin-Hsiu","family":"Chen","sequence":"first","affiliation":[]},{"given":"Cheng-Hsien","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Wen-Tse","family":"Chiu","sequence":"additional","affiliation":[]},{"given":"Chen-Mao","family":"Liao","sequence":"additional","affiliation":[]},{"given":"Yu-Ruei","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Shih-Kai","family":"Hung","sequence":"additional","affiliation":[]},{"given":"Liang-Cheng","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Hui-Ling","family":"Hsieh","sequence":"additional","affiliation":[]},{"given":"Wen-Yen","family":"Chiou","sequence":"additional","affiliation":[]},{"given":"Moon-Sing","family":"Lee","sequence":"additional","affiliation":[]},{"given":"Hon-Yi","family":"Lin","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0000-0002-3617-1739","authenticated-orcid":false,"given":"Wei-Min","family":"Liu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,29]]},"reference":[{"key":"11889_CR1","unstructured":"Bilic P, Christ PF et al (2019) The Liver Tumor Segmentation Benchmark (LiTS). arXiv:1901.04056"},{"key":"11889_CR2","doi-asserted-by":"crossref","unstructured":"Chen PH et al (2020) Attention-LSTM fused U-Net architecture for organ segmentation in CT images. International Symposium on Computer, Consumer and Control (IS3C)","DOI":"10.1109\/IS3C50286.2020.00085"},{"key":"11889_CR3","doi-asserted-by":"crossref","unstructured":"Huang H et al (2020) UNet 3+: A Full-Scale Connected UNet for Medical Image Segmentation. ICASSP 2020\u20132020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Barcelona, Spain, pp 1055\u20131059","DOI":"10.1109\/ICASSP40776.2020.9053405"},{"key":"11889_CR4","doi-asserted-by":"publisher","first-page":"4316","DOI":"10.1002\/mp.14386","volume":"47","author":"Y Liu","year":"2020","unstructured":"Liu Y, Lei Y, Fu Y, Wang T, Tang X, Jiang X, Curran WJ, Liu T, Patel P, Yang X (2020) CT-based multi-organ segmentation using a 3D self-attention U-Net network for pancreatic radiotherapy. Med Phys 47:4316\u20134324. https:\/\/doi.org\/10.1002\/mp.14386","journal-title":"Med Phys"},{"key":"11889_CR5","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1186\/1748-717X-7-160","volume":"7","author":"ML Macchia","year":"2012","unstructured":"Macchia ML et al (2012) Systematic evaluation of three different commercial software solutions for automatic segmentation for adaptive therapy in head-and-neck, prostate and pleural cancer. Radiat Oncol 7:160","journal-title":"Radiat Oncol"},{"issue":"17","key":"11889_CR6","doi-asserted-by":"publisher","first-page":"5381","DOI":"10.1088\/0031-9155\/57\/17\/5381","volume":"57","author":"AL Maitre","year":"2012","unstructured":"Maitre AL et al (2012) Impact of the accuracy of automatic tumour functional volume delineation on radiotherapy treatment planning. Phys Med Biol 57(17):5381\u20135397","journal-title":"Phys Med Biol"},{"issue":"7","key":"11889_CR7","doi-asserted-by":"publisher","first-page":"1417","DOI":"10.3109\/0284186X.2013.813069","volume":"52","author":"GC Mattiucci","year":"2013","unstructured":"Mattiucci GC, Boldrini L, Chiloiro G, D\u2019Agostino GR, Chiesa S, de Rose F, Azario L, Pasini D, Gambacorta MA, Balducci M, Valentini V (2013) Automatic delineation for replanning in nasopharynx radiotherapy: what is the agreement among experts to be considered as benchmark? Acta Oncol 52(7):1417\u20131422","journal-title":"Acta Oncol"},{"issue":"5","key":"11889_CR8","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1109\/TMI.2018.2881678","volume":"38","author":"AA Novikov","year":"2019","unstructured":"Novikov AA et al (2019) Deep sequential segmentation of organs in volumetric medical scans. IEEE Trans Med Imaging 38(5):1207\u20131215","journal-title":"IEEE Trans Med Imaging"},{"key":"11889_CR9","unstructured":"Oktay O, Schlemper J, Folgoc LL, Lee M, Heinrich M, Misawa K et al ( 2018) Attention u-net: Learning where to look for the pancreas. arXiv preprint arXiv:180403999"},{"key":"11889_CR10","volume-title":"International Conference on Medical image computing and computer-assisted intervention","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger O et al (2015) U-net: convolutional networks for biomedical image segmentation. In: International Conference on Medical image computing and computer-assisted intervention. Springer, Cham"},{"key":"11889_CR11","doi-asserted-by":"crossref","unstructured":"Shen C, Milletari F et al (2019) Improving V-Nets for multi-class abdominal organ segmentation. Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109490B","DOI":"10.1117\/12.2512790"},{"key":"11889_CR12","volume-title":"Proceedings of the 28th International Conference on Neural Information Processing Systems\u2014volume 1 (NIPS\u201915)","author":"X Shi","year":"2015","unstructured":"Shi X et al (2015) Convolutional LSTM Network: a machine learning approach for precipitation nowcasting. In: Proceedings of the 28th International Conference on Neural Information Processing Systems\u2014volume 1 (NIPS\u201915). MIT Press, Cambridge"},{"key":"11889_CR13","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1007\/978-3-319-67558-9_28","volume-title":"Deep learning in medical image analysis and multimodal learning for clinical decision support","author":"CH Sudre","year":"2017","unstructured":"Sudre CH et al (2017) Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations. In: Deep learning in medical image analysis and multimodal learning for clinical decision support. Springer, Cham, pp 240\u2013248"},{"issue":"1","key":"11889_CR14","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1186\/s12880-015-0068-x","volume":"15","author":"AA Taha","year":"2015","unstructured":"Taha AA, Hanbury A (2015) Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool. BMC Med Imaging 15(1):29","journal-title":"BMC Med Imaging"},{"key":"11889_CR15","doi-asserted-by":"crossref","unstructured":"Tang H et al 2021 Spatial context-aware self-attention model for multi-organ segmentation. arXiv:2012.09279, accepted by WACV","DOI":"10.1109\/WACV48630.2021.00098"},{"key":"11889_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101894","volume":"69","author":"Y Tang","year":"2021","unstructured":"Tang Y et al (2021) High-resolution 3D abdominal segmentation with random patch network fusion. Med Image Anal 69:101894","journal-title":"Med Image Anal"},{"key":"11889_CR17","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1186\/1748-717X-9-173","volume":"9","author":"D Thomson","year":"2014","unstructured":"Thomson D et al (2014) Evaluation of an automatic segmentation algorithm for definition of head and neck organs at risk. Radiat Oncol 9:173","journal-title":"Radiat Oncol"},{"key":"11889_CR18","first-page":"Article ID 9595","volume":"2020","author":"Z Tian","year":"2020","unstructured":"Tian Z et al (2020) A multiscale-based adjustable convolutional neural network for multiple organ segmentation. Wirel Commun Mob Comput 2020:Article ID 9595687 13 pages","journal-title":"Wirel Commun Mob Comput"},{"key":"11889_CR19","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.media.2019.04.005","volume":"55","author":"Y Wang","year":"2019","unstructured":"Wang Y, Zhou Y, Shen W, Park S, Fishman EK, Yuille AL (2019) Abdominal multi-organ segmentation with organ attention networks and statistical fusion. Med Image Anal 55:88\u2013102","journal-title":"Med Image Anal"},{"issue":"9","key":"11889_CR20","doi-asserted-by":"publisher","first-page":"5310","DOI":"10.1118\/1.4928485","volume":"42","author":"J Yang","year":"2015","unstructured":"Yang J, Beadle BM, Garden AS, Schwartz DL, Aristophanous M (2015) A multimodality segmentation framework for automatic target delineation in head and neck radiotherapy. Med Phys 42(9):5310\u20135320","journal-title":"Med Phys"},{"key":"11889_CR21","doi-asserted-by":"crossref","unstructured":"Yu L et al (2017) Volumetric ConvNets with mixed residual connections for automated prostate segmentation from 3D MR images. Thirty-first AAAI conference on artificial intelligence","DOI":"10.1609\/aaai.v31i1.10510"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-11889-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-11889-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-11889-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,25]],"date-time":"2023-01-25T05:27:21Z","timestamp":1674624441000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-11889-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,29]]},"references-count":21,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["11889"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-11889-7","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,29]]},"assertion":[{"value":"31 March 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 August 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 December 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 January 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No conflict of interest regarding to the manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of interest\/competing interests"}},{"value":"IRB number B10804010-1 approved by Tzu Chi Hospital in Chiayi, Taiwan.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}