A Mixed-attention Network for Automated Interventricular Septum Segmentation in Bright-blood Myocardial T2* MRI Relaxometry in Thalassemia.

Journal: Academic radiology
Published Date:

Abstract

RATIONALE AND OBJECTIVES: This study develops a deep-learning method for automatic segmentation of the interventricular septum (IS) in MR images to measure myocardial T2* and estimate cardiac iron deposition in patients with thalassemia.

Authors

  • Xiaofeng Wu
    The Three Departments of Medicine, Dayu County Peoples Hospital, Ganzhou, Jiangxi 341500, China.
  • Hangyu Wang
    School of Biomedical Engineering, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.); Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.); Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.).
  • Zeluan Chen
    School of Biomedical Engineering, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.); Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.); Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.).
  • Songsong Sun
    School of Biomedical Engineering, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.); Guangdong Provincial Key Laboratory of Medical Image Processing & Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.); Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence & Key Laboratory of Mental Health of the Ministry of Education, Southern Medical University, Guangzhou 510000, China (X.W., H.W., Z.C., S.S., Z.L., X.Z., Y.F.).
  • Zifeng Lian
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
  • Xinyuan Zhang
    Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, China.
  • Peng Peng
    School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Yanqiu Feng
    School of Biomedical Engineering, Southern Medical University, Guangzhou, China.

Keywords

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