Biopsy Needle Segmentation using Deep Networks on inhomogeneous Ultrasound Images
dc.cclicence | CC-BY-NC | en |
dc.contributor.author | Zhao, Yue | |
dc.contributor.author | Lu, Yi | |
dc.contributor.author | Lu, Xin | |
dc.contributor.author | Jing, J. | |
dc.contributor.author | Tao, L. | |
dc.contributor.author | Chen, X. | |
dc.date.acceptance | 2022-04-08 | |
dc.date.accessioned | 2022-05-17T12:02:02Z | |
dc.date.available | 2022-05-17T12:02:02Z | |
dc.date.issued | 2022-07-11 | |
dc.description.abstract | In minimally invasive interventional surgery, ultrasound imaging is usually used to provide real-time feedback in order to obtain the best diagnostic results or realize treatment plans, so how to accurately obtain the position of the medical biopsy needle is a problem worthy of study. 2D ultrasound simulation images containing the medical biopsy needle are generated, and our images background is from the real breast ultrasound image. Based on the deep learning network, the images containing the medical biopsy needle are used to analyze the effectiveness of different networks for needle localization for the purpose of returning needle positions in non-uniform ultrasound images. The results show that attention U-Net performed best and can accurately reflect the real position of the medical biopsy needle. The IoU and Precision can reach 90.19% and 96.25%, and the Angular Error is 0.40°. | en |
dc.funder | Other external funder (please detail below) | en |
dc.funder.other | Natural Science Foundation of China (62173116) | en |
dc.funder.other | Postdoctoral Research Funds of Heilongjiang Province (Grant No. LBH-TZ13 and No. LBH-Z15068) | en |
dc.funder.other | Postdoctoral initial funding of Heilongjiang Province (No. LBH-Q21097) | en |
dc.funder.other | egree & Postgraduate Education Reform Project of Harbin Institute of Technology (No. 21MS002) | en |
dc.identifier.citation | Zhao, Y., Lu, Y., Lu, X., Jing, J., Tao, L., Chen, X. (2022) Biopsy Needle Segmentation using Deep Networks on inhomogeneous Ultrasound Images. 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2022), Glasgow, July 2022. | en |
dc.identifier.doi | https://doi.org/10.1109/embc48229.2022.9871059 | |
dc.identifier.uri | https://hdl.handle.net/2086/21889 | |
dc.language.iso | en | en |
dc.peerreviewed | Yes | en |
dc.projectid | 62173116) | en |
dc.projectid | Grant No. LBH-TZ13 and No. LBH-Z15068 | en |
dc.projectid | No. LBH-Q21097 | en |
dc.projectid | No. 21MS002 | en |
dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
dc.subject | deep network | en |
dc.subject | 2D ultrasound images | en |
dc.subject | biopsy needle | en |
dc.title | Biopsy Needle Segmentation using Deep Networks on inhomogeneous Ultrasound Images | en |
dc.type | Conference | en |
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