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  • 标题:Improvement of Statistical Shape Models for Soft Tissues Using Modified-Coherent Point Drift
  • 本地全文:下载
  • 作者:Mahdi Delavari ; Amir Hossein Foruzan ; Yen-Wei Chen
  • 期刊名称:IFAC PapersOnLine
  • 印刷版ISSN:2405-8963
  • 出版年度:2015
  • 卷号:48
  • 期号:20
  • 页码:36-41
  • DOI:10.1016/j.ifacol.2015.10.111
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper, we present a method to build statistical shape models for soft tissues. The efficiency of the model is close to the models built by the MDL (Minimum Description Length) algorithm; however, our method is much faster. The core of our method is based on finding corresponding points by a modified Coherent Point Drift method. The conventional CPD algorithm is modified to prepare a robust methods to find corresponding points of soft tissues. Our method achieved the Compactness, Generality, and Specificity of 18, 3.64(±0.85) mm, and 0.21(±0.06) respectively. Our results are close to the MDL results. The run-time of our method is 68 seconds which is faster than the MDL (3600 seconds) and TPS-RPM (390 seconds) methods.
  • 关键词:KeywordsCorresponding pointsStatistical Shape ModelsModified Coherent Point DriftMedical Image Registration
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