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Chinese Journal of Biomedical Engineering  2022, Vol. 41 Issue (1): 64-72    DOI: 10.3969/j.issn.0258-8021.2022.01.008
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Study of Ultrasonic Thyroid Nodules Detection Based on Cascade Rcnn
Zhang Haowei1*, Li Zhanqi1, Liu Ying1, Li Miao2
1(School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China)
2(Zhengzhou Yihe Hospital of Henan Province, Zhengzhou 450000, China)
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Abstract  Thyroid ultrasound images have low contrast, unclear edges, high noise, and the surrounding tissues are complex and difficult to distinguish, making it extremely difficult for doctors to diagnose thyroid diseases. To overcome this problem, Cascade Rcnn target detection algorithm was used in this work, with ResNet50, Resnet101 and fusion compression incentive attention modules SE-ResNet50, SE-ReNet101 as the backbone network. There were 1 513 cases thyroid ultrasound images (including 832 cases benign nodules and 681 cases malignant nodules) obtained from a third-class hospital. Under the guidance of professional sonographers, the data were preprocessed into the standard coco format data set. The weights obtained from the pre-training of the large Imagenet database by transfer learning were migrated to this experimental model structure. Comparing with the experimental results of the four backbone networks, Cascade Rcnn algorithm with SE-ResNet101 as the backbone network achieved an accuracy of 92.4%, recall rate of 86.2%, specificity of 95.1%1, F1 value of 89.22%, and mAP value of 82.4%. The detection result of nodule localization and classification of benign and malignant was of clinical guiding significance for assisting doctors in the diagnosis of thyroid ultrasound images.
Key wordsthyroid ultrasound image      Cascade Rcnn      target detection      transfer learning     
Received: 31 December 2020     
PACS:  R318  
Corresponding Authors: * E-mail: haowiezh@aliyun.com   
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Zhang Haowei
Li Zhanqi
Liu Ying
Li Miao
Cite this article:   
Zhang Haowei,Li Zhanqi,Liu Ying, et al. Study of Ultrasonic Thyroid Nodules Detection Based on Cascade Rcnn[J]. Chinese Journal of Biomedical Engineering, 2022, 41(1): 64-72.
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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021.2022.01.008     OR     http://cjbme.csbme.org/EN/Y2022/V41/I1/64
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