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Title: X-ray computed tomography using curvelet sparse regularization

Purpose: Reconstruction of x-ray computed tomography (CT) data remains a mathematically challenging problem in medical imaging. Complementing the standard analytical reconstruction methods, sparse regularization is growing in importance, as it allows inclusion of prior knowledge. The paper presents a method for sparse regularization based on the curvelet frame for the application to iterative reconstruction in x-ray computed tomography. Methods: In this work, the authors present an iterative reconstruction approach based on the alternating direction method of multipliers using curvelet sparse regularization. Results: Evaluation of the method is performed on a specifically crafted numerical phantom dataset to highlight the method’s strengths. Additional evaluation is performed on two real datasets from commercial scanners with different noise characteristics, a clinical bone sample acquired in a micro-CT and a human abdomen scanned in a diagnostic CT. The results clearly illustrate that curvelet sparse regularization has characteristic strengths. In particular, it improves the restoration and resolution of highly directional, high contrast features with smooth contrast variations. The authors also compare this approach to the popular technique of total variation and to traditional filtered backprojection. Conclusions: The authors conclude that curvelet sparse regularization is able to improve reconstruction quality by reducing noise while preserving highly directionalmore » features.« less
Authors:
; ;  [1] ; ;  [2] ; ;  [3] ; ;  [4]
  1. Chair for Computer Aided Medical Procedures (CAMP), Technische Universität München, 85748, Garching (Germany)
  2. Institute of Computational Biology, Helmholtz Zentrum München, 85764, Neuherberg (Germany)
  3. Lehrstuhl für Biomedizinische Physik, Physik-Department and Institut für Medizintechnik, Technische Universität München, 85748, Garching (Germany)
  4. Department of Diagnostic and Interventional Radiology, Klinikum Rechts der Isar, Technische Universität München, 81675, München (Germany)
Publication Date:
OSTI Identifier:
22413490
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 4; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 60 APPLIED LIFE SCIENCES; ABDOMEN; COMPARATIVE EVALUATIONS; COMPUTERIZED TOMOGRAPHY; DATASETS; FILTERS; ITERATIVE METHODS; NOISE; PHANTOMS; X RADIATION