Regularization Methods for the Analytical Statistical Reconstruction Problem in Medical Computed Tomography

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• 关键词：Image reconstruction from projections ; X ; ray computed tomography ; Statistical reconstruction algorithm ; Overfitting ; Regularization
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9693
• 期：1
• 页码：147-158
• 全文大小：1,487 KB
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• 作者单位：Robert Cierniak (19)
  Anna Lorent (19)
  Piotr Pluta (19)
  Nimit Shah (20)
  
  19. Institute of Computational Intelligence, Czestochowa University of Technology, Armii Krajowej 36, 42-200, Czestochowa, Poland
  20. Department of Electrical Engineering, M.S. University of Baroda, Vadodara, India
  
• 丛书名：Artificial Intelligence and Soft Computing
• ISBN：978-3-319-39384-1
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9693

文摘

The main purpose of this paper is to present the properties of our novel statistical model-based iterative approach to the image reconstruction from projections problem regarding its condition number. The reconstruction algorithm based on this concept uses a maximum likelihood estimation with an objective adjusted to the probability distribution of measured signals obtained using x-ray computed tomography. We compare this with some selected methods of regularizing the problem. The concept presented here is fundamental for 3D statistical tailored reconstruction methods designed for x-ray computed tomography.