{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T00:56:05Z","timestamp":1790297765601,"version":"4.1.0"},"reference-count":43,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Medical Image Analysis"],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1016\/j.media.2023.102905","type":"journal-article","created":{"date-parts":[[2023,7,13]],"date-time":"2023-07-13T13:34:10Z","timestamp":1689255250000},"page":"102905","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":38,"special_numbering":"C","title":["TS-DSANN: Texture and shape focused dual-stream attention neural network for benign-malignant diagnosis of thyroid nodules in ultrasound images"],"prefix":"10.1016","volume":"89","author":[{"given":"Lu","family":"Tang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuangeng","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6556-6556","authenticated-orcid":false,"given":"Hang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiming","family":"Cui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3756-8885","authenticated-orcid":false,"given":"Yu","family":"Hui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dinggang","family":"Shen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.media.2023.102905_bib0002","first-page":"452","article-title":"Automated benign & malignant thyroid lesion characterization and classification in 3D contrast-enhanced ultrasound","volume":"2012","author":"Acharya","year":"2012","journal-title":"Annu. Int. Conf. IEEE Eng. Med. Biol. Soc."},{"issue":"2","key":"10.1016\/j.media.2023.102905_bib0001","doi-asserted-by":"crossref","first-page":"245","DOI":"10.7863\/ultra.33.2.245","article-title":"Computer-Aided diagnostic system for detection of hashimoto thyroiditis on ultrasound images from a polish population","volume":"33","author":"Acharya","year":"2014","journal-title":"J. Ultras. Med."},{"key":"10.1016\/j.media.2023.102905_bib0003","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"1124","article-title":"On the performance of GoogLeNet and AlexNet applied to sketches","author":"Ballester","year":"2016"},{"issue":"3","key":"10.1016\/j.media.2023.102905_bib0004","doi-asserted-by":"crossref","first-page":"695","DOI":"10.1148\/radiol.2019181343","article-title":"Management of thyroid nodules seen on US images: deep learning may match performance of radiologists","volume":"292","author":"Buda","year":"2019","journal-title":"Radiology"},{"issue":"24","key":"10.1016\/j.media.2023.102905_bib0005","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1056\/NEJMcp1415786","article-title":"Thyroid nodules","volume":"373","author":"Burman","year":"2015","journal-title":"N. Engl. J. Med."},{"key":"10.1016\/j.media.2023.102905_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2022.106453","article-title":"Hybrid transformer UNet for thyroid segmentation from ultrasound scans","volume":"153","author":"Chi","year":"2023","journal-title":"Comput. Biol. Med."},{"issue":"9","key":"10.1016\/j.media.2023.102905_bib0007","doi-asserted-by":"crossref","first-page":"914","DOI":"10.1001\/jama.2018.0898","article-title":"The diagnosis and management of thyroid nodules","volume":"319","author":"Durante","year":"2018","journal-title":"JAMA J. Am. Med. Assoc."},{"key":"10.1016\/j.media.2023.102905_bib0008","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"10705","article-title":"Attention branch network: learning of attention mechanism for visual explanation","author":"Fukui","year":"2019"},{"key":"10.1016\/j.media.2023.102905_bib0009","series-title":"Proceedings of the Advances in Neural Information Processing Systems (NIPS)","first-page":"262","article-title":"Texture synthesis using convolutional neural networks","author":"Gatys","year":"2015"},{"key":"10.1016\/j.media.2023.102905_bib0010","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","author":"Geirhos","year":"2019"},{"key":"10.1016\/j.media.2023.102905_bib0011","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"3705","article-title":"AFS: an attention-based mechanism for supervised feature selection","author":"Gui","year":"2019"},{"key":"10.1016\/j.media.2023.102905_bib0012","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"770","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.media.2023.102905_bib0013","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"1923","article-title":"Assessing shape bias property of convolutional neural networks","author":"Hosseini","year":"2018"},{"key":"10.1016\/j.media.2023.102905_bib0014","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"695","article-title":"Seed, expand and constrain: three principles for weakly-supervised image segmentation","author":"Kolesnikov","year":"2016"},{"issue":"2","key":"10.1016\/j.media.2023.102905_bib0015","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1146\/annurev-vision-082114-035447","article-title":"Deep neural networks: a new framework for modelling biological vision and brain information processing","volume":"45","author":"Kriegeskorte","year":"2015","journal-title":"Annu. Rev. Vis. Sci."},{"issue":"3","key":"10.1016\/j.media.2023.102905_bib0016","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1634\/theoncologist.2009-0324","article-title":"Use of ultrasound in the management of thyroid cancer","volume":"15","author":"Lew","year":"2010","journal-title":"Oncologist"},{"issue":"2","key":"10.1016\/j.media.2023.102905_bib0017","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/S1470-2045(18)30762-9","article-title":"Diagnosis of thyroid cancer using deep convolutional neural network models applied to sonographic images: a retrospective, multicohort, diagnostic study","volume":"20","author":"Li","year":"2019","journal-title":"Lancet Oncol."},{"key":"10.1016\/j.media.2023.102905_bib0019","series-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"919","article-title":"Classification of thyroid nodules in ultrasound images using deep model based transfer learning and hybrid features","author":"Liu","year":"2017"},{"key":"10.1016\/j.media.2023.102905_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2019.101555","article-title":"Automated detection and classification of thyroid nodules in ultrasound images using clinical-knowledge-guided convolutional neural networks","volume":"58","author":"Liu","year":"2019","journal-title":"Med. Image Anal."},{"issue":"7","key":"10.1016\/j.media.2023.102905_bib0020","doi-asserted-by":"crossref","first-page":"e411","DOI":"10.1016\/S2589-7500(21)00107-2","article-title":"A deep-learning model to assist thyroid nodule diagnosis and management","volume":"3","author":"Liu","year":"2021","journal-title":"Lancet Digit. Health"},{"key":"10.1016\/j.media.2023.102905_bib0021","doi-asserted-by":"crossref","first-page":"1582","DOI":"10.1109\/JBHI.2022.3153559","article-title":"GAN-Guided deformable attention network for identifying thyroid nodules in ultrasound images","volume":"26","author":"Lu","year":"2022","journal-title":"IEEE J. Biomed. Health"},{"key":"10.1016\/j.media.2023.102905_bib0022","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.ultras.2016.09.011","article-title":"A pre-trained convolutional neural network based method for thyroid nodule diagnosis","volume":"73","author":"Ma","year":"2017","journal-title":"Ultrasonics"},{"key":"10.1016\/j.media.2023.102905_bib0023","series-title":"Proceedings of the IEEE Conference Computer Vision and Pattern Recognition (CVPR)","article-title":"Lightweight residual network for the classification of thyroid nodules","author":"Nikhila","year":"2019"},{"issue":"3","key":"10.1016\/j.media.2023.102905_bib0024","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.jksuci.2019.01.007","article-title":"Computer aided diagnosis for thyroid cancer system based on internal and external characteristics","volume":"33","author":"Nugroho","year":"2021","journal-title":"J. King Saud Univ. Comput."},{"issue":"10","key":"10.1016\/j.media.2023.102905_bib0025","doi-asserted-by":"crossref","first-page":"2698","DOI":"10.1109\/TMI.2020.3042773","article-title":"Learning hierarchical attention for weakly-supervised chest x-ray abnormality localization and diagnosis","volume":"40","author":"Ouyang","year":"2021","journal-title":"IEEE T. Med. Imaging"},{"issue":"7","key":"10.1016\/j.media.2023.102905_bib0026","doi-asserted-by":"crossref","first-page":"e250","DOI":"10.1016\/S2589-7500(21)00041-8","article-title":"Deep learning-based artificial intelligence model to assist thyroid nodule diagnosis and management: a multicentre diagnostic study","volume":"3","author":"Peng","year":"2021","journal-title":"Lancet Digit. Health"},{"key":"10.1016\/j.media.2023.102905_bib0027","doi-asserted-by":"crossref","DOI":"10.1155\/2018\/8087624","article-title":"Evaluation of commonly used algorithms for thyroid ultrasound images segmentation and improvement using machine learning approaches","author":"Poudel","year":"2018","journal-title":"J. Healthc. Eng."},{"key":"10.1016\/j.media.2023.102905_bib0028","series-title":"Proceedings of the International Conference on Machine Learning","first-page":"2940","article-title":"Cognitive psychology for deep neural networks: a shape bias case study","author":"Ritter","year":"2017"},{"key":"10.1016\/j.media.2023.102905_bib0029","series-title":"Proceedings of the Medical Image Computing and Computer-Assisted Intervention (MICCAI)","first-page":"234","article-title":"U-Net: convolutional networks for biomedical image segmentation","author":"Ronneberger","year":"2015"},{"key":"10.1016\/j.media.2023.102905_bib0030","series-title":"Proceedings of the IEEE International Conference on Computer Vision (ICCV)","first-page":"618","article-title":"Grad-CAM: visual explanations from deep networks via gradient-based localization","author":"Selvaraju","year":"2017"},{"key":"10.1016\/j.media.2023.102905_bib0031","doi-asserted-by":"crossref","first-page":"64064","DOI":"10.1109\/ACCESS.2020.2982767","article-title":"Thyroid nodule ultrasound image classification through hybrid feature cropping network","volume":"8","author":"Song","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"10.1016\/j.media.2023.102905_bib0032","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"issue":"3","key":"10.1016\/j.media.2023.102905_bib0033","doi-asserted-by":"crossref","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries","volume":"71","author":"Sung","year":"2021","journal-title":"CA-Cancer J. Clin."},{"issue":"1","key":"10.1016\/j.media.2023.102905_bib0034","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1148\/radiol.2017171240","article-title":"Thyroid imaging reporting and data system (TI-RADS): a user\u2019s guide","volume":"287","author":"Tessler","year":"2018","journal-title":"Radiology"},{"issue":"2","key":"10.1016\/j.media.2023.102905_bib0035","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/j.compmedimag.2008.10.010","article-title":"Morphological and wavelet features towards sonographic thyroid nodules evaluation","volume":"33","author":"Tsantis","year":"2009","journal-title":"Comput. Med. Imag. Grap."},{"key":"10.1016\/j.media.2023.102905_bib0036","doi-asserted-by":"crossref","first-page":"907","DOI":"10.3389\/fendo.2019.00907","article-title":"Nodular thyroid disease in the era of precision medicine","volume":"10","author":"Tumino","year":"2020","journal-title":"Front. Endocrinol."},{"key":"10.1016\/j.media.2023.102905_bib0037","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"3156","article-title":"Residual attention network for image classification","author":"Wang","year":"2017"},{"key":"10.1016\/j.media.2023.102905_bib0038","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2020.101665","article-title":"Automatic diagnosis for thyroid nodules in ultrasound images by deep neural networks","volume":"61","author":"Wang","year":"2020","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.media.2023.102905_bib0039","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2020.104064","article-title":"Integrate domain knowledge in training multi-task cascade deep learning model for benign-malignant thyroid nodule classification on ultrasound images","volume":"98","author":"Yang","year":"2021","journal-title":"Eng. Appl. Artif. Intel."},{"key":"10.1016\/j.media.2023.102905_bib0040","series-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Paying more attention to attention: improving the performance of convolutional neural networks via attention transfer","author":"Zagoruyko","year":"2017"},{"issue":"12","key":"10.1016\/j.media.2023.102905_bib0041","doi-asserted-by":"crossref","first-page":"2993","DOI":"10.1002\/jum.16006","article-title":"Classification of thyroid nodules by using deep learning radiomics based on ultrasound dynamic video","volume":"41","author":"Zhang","year":"2022","journal-title":"J. Ultrasound Med."},{"key":"10.1016\/j.media.2023.102905_bib0042","series-title":"Proceedings of the Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)","first-page":"129","article-title":"Cascade UNet and CH-UNet for thyroid nodule segmentation and benign and malignant classification","author":"Zhang","year":"2021"},{"key":"10.1016\/j.media.2023.102905_bib0043","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"2921","article-title":"Learning deep features for discriminative localization","author":"Zhou","year":"2016"}],"container-title":["Medical Image Analysis"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841523001652?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1361841523001652?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T18:58:02Z","timestamp":1761245882000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1361841523001652"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10]]},"references-count":43,"alternative-id":["S1361841523001652"],"URL":"https:\/\/doi.org\/10.1016\/j.media.2023.102905","relation":{},"ISSN":["1361-8415"],"issn-type":[{"value":"1361-8415","type":"print"}],"subject":[],"published":{"date-parts":[[2023,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"TS-DSANN: Texture and shape focused dual-stream attention neural network for benign-malignant diagnosis of thyroid nodules in ultrasound images","name":"articletitle","label":"Article Title"},{"value":"Medical Image Analysis","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.media.2023.102905","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"102905"}}