Segmentation of Multiple Structures in Chest Radiographs Using Multi-task Fully Convolutional Networks
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-319-59129-2_24
Reference15 articles.
1. Kakeda, S., Moriya, J., Sato, H., Aoki, T., Watanabe, H., Nakata, H., Oda, N., Katsuragawa, S., Yamamoto, K., Doi, K.: Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. Am. J. Roentgenol. 182, 505–510 (2004)
2. Melendez, J., Sánchez, C.I., Philipsen, R.H.H.M., Maduskar, P., Dawson, R., Theron, G., Dheda, K., van Ginneken, B.: An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information. Sci. Rep. 6, 25265 (2016)
3. van Ginneken, B., Stegmann, M.B., Loog, M.: Segmentation of anatomical structures in chest radiographs using supervised methods: a comparative study on a public database. Med. Image Anal. 10, 19–40 (2006)
4. Shao, Y., Gao, Y., Guo, Y., Shi, Y., Yang, X., Shen, D.: Hierarchical lung field segmentation with joint shape and appearance sparse learning. IEEE Trans. Med. Imaging 33, 1761–1780 (2014)
5. Ibragimov, B., Likar, B., Pernuš, F., Vrtovec, T.: Accurate landmark-based segmentation by incorporating landmark misdetections. In: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), pp. 1072–1075. IEEE (2016)
Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Dual center validation of deep learning for automated multi-label segmentation of thoracic anatomy in bedside chest radiographs;Computer Methods and Programs in Biomedicine;2023-06
2. Semi-supervised Multi-structure Segmentation in Chest X-Ray Imaging;2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS);2023-06
3. A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest X-ray images;Scientific Reports;2023-01-16
4. Multi-stage Synthetic Image Generation for the Semantic Segmentation of Medical Images;Intelligent Systems Reference Library;2022-09-27
5. Development of a multi-task learning V-Net for pulmonary lobar segmentation on CT and application to diseased lungs;Clinical Radiology;2022-08
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3