89 / 2021-10-25 19:21:45
Cone Beam CT Series Images Rigid Registration for Temporomandibular Joint via Self-supervised Learning Network
medical image processing,rigid registration,temporomandibular joint,cone beam CT images,self-supervised learning
终稿
Shuai Wang / Beijing Jiaotong University, School of Electronic and Information Engineering
Jupeng Li / Beijing Jiaotong University, School of Electronic and Information Engineering
Yahui Peng / Beijing Jiaotong University, School of Electronic and Information Engineering
JiLing Feng / Department of Oral and Maxillofacial Radiology Peking University School and Hospital of Stomatology Beijing, China
Ruohan Ma / Department of Oral and Maxillofacial Radiology Peking University School and Hospital of Stomatology Beijing, China
Gang Li / Department of Oral and Maxillofacial Radiology Peking University School and Hospital of Stomatology Beijing, China
Registration of the temporomandibular joint (TMJ) cone beam CT (CBCT) images plays an important role in the medical treatment of temporomandibular joint disorders (TMD) and related diseases. To highlight changes in the condyle bone of TMJ, accurate CBCT images registration is still a challenging work. In this paper, we proposed a self-supervised learning network to realize rigid registration for the TMJ CBCT series images. Without adopting the method of optimization iteration and similarity measurement, the transformation parameters of the rigid registration are directly regressed through our network. Then the warped image is obtained through spatial transformer network. The experimental results also proved the feasibility of this method, and it can greatly improve the accuracy and processing speed of rigid registration.
重要日期
  • 会议日期

    11月13日

    2021

    11月14日

    2021

  • 09月30日 2021

    报告提交截止日期

  • 11月14日 2021

    注册截止日期

主办单位
IEEE北京分会
中国生物医学工程学会医学物理分会
中国电子学会生命电子学分会
承办单位
中国科学技术大学
安徽省生物医学工程学会
联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询