{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T22:30:45Z","timestamp":1774045845760,"version":"3.50.1"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100022963","name":"Key Research and Development Program of Zhejiang Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100022963","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003467","name":"Hangzhou Dianzi University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003467","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Visual Communication and Image Representation"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.jvcir.2026.104760","type":"journal-article","created":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:44:38Z","timestamp":1772264678000},"page":"104760","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["X-ray image translation based on weakly supervised CycleGAN"],"prefix":"10.1016","volume":"117","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9159-9471","authenticated-orcid":false,"given":"Xiaolong","family":"Zheng","sequence":"first","affiliation":[]},{"given":"Ziteng","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Ji","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Huanhuan","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Liang","family":"Zheng","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.jvcir.2026.104760_b1","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1002\/rob.21918","article-title":"A survey of deep learning techniques for autonomous driving","volume":"37","author":"Grigorescu","year":"2020","journal-title":"J. Field Robot."},{"key":"10.1016\/j.jvcir.2026.104760_b2","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2020.113816","article-title":"Self-driving cars: A survey","volume":"165","author":"Badue","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.jvcir.2026.104760_b3","series-title":"Towards cognitive exploration through deep reinforcement learning for mobile robots","author":"Tai","year":"2016"},{"issue":"7","key":"10.1016\/j.jvcir.2026.104760_b4","first-page":"1","article-title":"An overview of interactive medical image segmentation","volume":"2013","author":"Zhao","year":"2013","journal-title":"Ann. BMVA"},{"issue":"2","key":"10.1016\/j.jvcir.2026.104760_b5","doi-asserted-by":"crossref","first-page":"309","DOI":"10.3390\/jpm12020309","article-title":"A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation","volume":"12","author":"Allioui","year":"2022","journal-title":"J. Pers. Med."},{"key":"10.1016\/j.jvcir.2026.104760_b6","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2021.108245","article-title":"Towards automatic threat detection: A survey of advances of deep learning within X-ray security imaging","volume":"122","author":"Akcay","year":"2022","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.jvcir.2026.104760_b7","doi-asserted-by":"crossref","unstructured":"Y. Wei, R. Tao, Z. Wu, Y. Ma, L. Zhang, X. Liu, Occluded prohibited items detection: An x-ray security inspection benchmark and de-occlusion attention module, in: Proceedings of the 28th ACM International Conference on Multimedia, 2020, pp. 138\u2013146.","DOI":"10.1145\/3394171.3413828"},{"issue":"12","key":"10.1016\/j.jvcir.2026.104760_b8","doi-asserted-by":"crossref","first-page":"2644","DOI":"10.3390\/electronics12122644","article-title":"X-ray security inspection image dangerous goods detection algorithm based on improved yolov4","volume":"12","author":"Yu","year":"2023","journal-title":"Electronics"},{"issue":"8","key":"10.1016\/j.jvcir.2026.104760_b9","doi-asserted-by":"crossref","first-page":"4069","DOI":"10.3390\/s23084069","article-title":"FSVM: A few-shot threat detection method for x-ray security images","volume":"23","author":"Fang","year":"2023","journal-title":"Sensors"},{"key":"10.1016\/j.jvcir.2026.104760_b10","first-page":"03003","article-title":"Automated lung semantic segmentation on x-ray using convolutional models","volume":"vol. 44","author":"Ramesh","year":"2022"},{"key":"10.1016\/j.jvcir.2026.104760_b11","article-title":"Generative adversarial nets","volume":"27","author":"Goodfellow","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.jvcir.2026.104760_b12","doi-asserted-by":"crossref","unstructured":"X. Mao, Q. Li, H. Xie, R.Y. Lau, Z. Wang, S. Paul Smolley, Least squares generative adversarial networks, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 2794\u20132802.","DOI":"10.1109\/ICCV.2017.304"},{"key":"10.1016\/j.jvcir.2026.104760_b13","unstructured":"M. Arjovsky, S. Chintala, L. Bottou, Wasserstein generative adversarial networks, in: International Conference on Machine Learning, PMLR, 2017, pp. 214\u2013223."},{"key":"10.1016\/j.jvcir.2026.104760_b14","article-title":"Improved training of wasserstein gans","volume":"30","author":"Gulrajani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.jvcir.2026.104760_b15","series-title":"Conditional generative adversarial nets","author":"Mirza","year":"2014"},{"issue":"7","key":"10.1016\/j.jvcir.2026.104760_b16","doi-asserted-by":"crossref","first-page":"2553","DOI":"10.1109\/TMI.2020.2974159","article-title":"Image-to-images translation for multi-task organ segmentation and bone suppression in chest X-ray radiography","volume":"39","author":"Eslami","year":"2020","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"4","key":"10.1016\/j.jvcir.2026.104760_b17","doi-asserted-by":"crossref","first-page":"897","DOI":"10.1109\/TMI.2022.3218568","article-title":"X-ray to DRR images translation for efficient multiple objects similarity measures in deformable model 3D\/2D registration","volume":"42","author":"Aubert","year":"2022","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"10","key":"10.1016\/j.jvcir.2026.104760_b18","doi-asserted-by":"crossref","first-page":"3961","DOI":"10.3390\/app14103961","article-title":"Enhancing x-ray security image synthesis: Advanced generative models and innovative data augmentation techniques","volume":"14","author":"Yagoub","year":"2024","journal-title":"Appl. Sci."},{"key":"10.1016\/j.jvcir.2026.104760_b19","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1007\/s11548-020-02159-2","article-title":"pix2xray: Converting RGB images into x-rays using generative adversarial networks","volume":"15","author":"Haiderbhai","year":"2020","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"key":"10.1016\/j.jvcir.2026.104760_b20","first-page":"1","article-title":"Mri to pet image synthesis using modified pix2pix for alzheimer\u2019s disease diagnosis","author":"Meharban","year":"2025","journal-title":"Chin. J. Acad. Radiol."},{"issue":"24","key":"10.1016\/j.jvcir.2026.104760_b21","doi-asserted-by":"crossref","first-page":"9628","DOI":"10.3390\/s22249628","article-title":"Image translation by Ad CycleGAN for COVID-19 X-ray images: A new approach for controllable GAN","volume":"22","author":"Liang","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.jvcir.2026.104760_b22","doi-asserted-by":"crossref","unstructured":"P. Isola, J.-Y. Zhu, T. Zhou, A.A. Efros, Image-to-image translation with conditional adversarial networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017, pp. 1125\u20131134.","DOI":"10.1109\/CVPR.2017.632"},{"key":"10.1016\/j.jvcir.2026.104760_b23","doi-asserted-by":"crossref","unstructured":"J.-Y. Zhu, T. Park, P. Isola, A.A. Efros, Unpaired image-to-image translation using cycle-consistent adversarial networks, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 2223\u20132232.","DOI":"10.1109\/ICCV.2017.244"},{"key":"10.1016\/j.jvcir.2026.104760_b24","unstructured":"J. Kim, M. Kim, H. Kang, K.H. Lee, U-GAT-IT: Unsupervised generative attentional networks with adaptive layer-instance normalization for image-to-image translation, in: International Conference on Learning Representations, 2020."},{"key":"10.1016\/j.jvcir.2026.104760_b25","doi-asserted-by":"crossref","unstructured":"D. Torbunov, Y. Huang, H. Yu, J. Huang, S. Yoo, M. Lin, B. Viren, Y. Ren, UVCGAN: UNet vision transformer cycle-consistent GAN for unpaired image-to-image translation, in: Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision, 2023, pp. 702\u2013712.","DOI":"10.1109\/WACV56688.2023.00077"},{"key":"10.1016\/j.jvcir.2026.104760_b26","doi-asserted-by":"crossref","unstructured":"Z. Yi, H. Zhang, P. Tan, M. Gong, DualGAN: Unsupervised dual learning for image-to-image translation, in: Proceedings of the IEEE International Conference on Computer Vision, 2017, pp. 2849\u20132857.","DOI":"10.1109\/ICCV.2017.310"},{"key":"10.1016\/j.jvcir.2026.104760_b27","unstructured":"D. Torbunov, et al. UVCGAN v2: An improved cycle-consistent GAN for unpaired image-to-image translation, arXiv preprint arXiv:2303.16280."},{"key":"10.1016\/j.jvcir.2026.104760_b28","series-title":"Medical Image Computing and Computer-Assisted Intervention MICCAI 2015: 18th International Con- Ference, Munich, Germany, October 5\u20139, 2015, Proceedings, Part III 18","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.jvcir.2026.104760_b29","doi-asserted-by":"crossref","unstructured":"K. He, X. Zhang, S. Ren, J. Sun, Deep residual learning for image recognition, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016, pp. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"10.1016\/j.jvcir.2026.104760_b30","unstructured":"A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly, et al., An image is worth 16x16 words: Transformers for image recognition at scale, in: International Conference on Learning Representations, 2020."},{"key":"10.1016\/j.jvcir.2026.104760_b31","doi-asserted-by":"crossref","unstructured":"Y. Choi, M. Choi, M. Kim, J.-W. Ha, S. Kim, J. Choo, StarGAN: Unified generative adversarial networks for multi-domain image-to-image translation, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 8789\u20138797.","DOI":"10.1109\/CVPR.2018.00916"},{"key":"10.1016\/j.jvcir.2026.104760_b32","doi-asserted-by":"crossref","unstructured":"Y. Choi, Y. Uh, J. Yoo, J.-W. Ha, StarGAN v2: Diverse image synthesis for multiple domains, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 8188\u20138197.","DOI":"10.1109\/CVPR42600.2020.00821"},{"key":"10.1016\/j.jvcir.2026.104760_b33","doi-asserted-by":"crossref","unstructured":"S. Xie, Y. Xu, M. Gong, K. Zhang, Unpaired image-to-image translation with shortest path regularization, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 10177\u201310187.","DOI":"10.1109\/CVPR52729.2023.00981"},{"key":"10.1016\/j.jvcir.2026.104760_b34","doi-asserted-by":"crossref","unstructured":"X. Chen, C. Xu, X. Yang, D. Tao, Attention-gan for object transfiguration in wild images, in: Proceedings of the European Conference on Computer Vision, ECCV, 2018, pp. 164\u2013180.","DOI":"10.1007\/978-3-030-01216-8_11"},{"key":"10.1016\/j.jvcir.2026.104760_b35","unstructured":"A. Almahairi, S. Rajeshwar, A. Sordoni, P. Bachman, A. Courville, Augmented cyclegan: Learning many-to-many mappings from unpaired data, in: International Conference on Machine Learning, PMLR, 2018, pp. 195\u2013204."},{"key":"10.1016\/j.jvcir.2026.104760_b36","article-title":"GANs trained by a two time-scale update rule converge to a local nash equilibrium","volume":"30","author":"Heusel","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.jvcir.2026.104760_b37","unstructured":"M. Bi\u0144kowski, D.J. Sutherland, M. Arbel, A. Gretton, Demystifying MMD GANs, in: International Conference on Learning Representations, 2018."},{"key":"10.1016\/j.jvcir.2026.104760_b38","doi-asserted-by":"crossref","unstructured":"Z. Zhang, L. Yang, Y. Zheng, Translating and segmenting multimodal medical volumes with cycle-and shape-consistency generative adversarial network, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 9242\u20139251.","DOI":"10.1109\/CVPR.2018.00963"},{"issue":"4","key":"10.1016\/j.jvcir.2026.104760_b39","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: From error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.jvcir.2026.104760_b40","doi-asserted-by":"crossref","unstructured":"R. Zhang, P. Isola, A.A. Efros, E. Shechtman, O. Wang, The unreasonable effectiveness of deep features as a perceptual metric, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2018, pp. 586\u2013595.","DOI":"10.1109\/CVPR.2018.00068"}],"container-title":["Journal of Visual Communication and Image Representation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1047320326000556?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1047320326000556?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T20:58:54Z","timestamp":1774040334000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1047320326000556"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":40,"alternative-id":["S1047320326000556"],"URL":"https:\/\/doi.org\/10.1016\/j.jvcir.2026.104760","relation":{},"ISSN":["1047-3203"],"issn-type":[{"value":"1047-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"X-ray image translation based on weakly supervised CycleGAN","name":"articletitle","label":"Article Title"},{"value":"Journal of Visual Communication and Image Representation","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.jvcir.2026.104760","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"104760"}}