Computational Methods for Molecular Imaging

  • Fei Gao
  • Kuangyu Shi
  • Shuo Li

Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 22)

Table of contents

  1. Front Matter
    Pages i-vii
  2. Computational Methods

    1. Front Matter
      Pages 1-1
    2. Fei Gao, Pengcheng Shi
      Pages 3-14
    3. Ziyue Xu, Ulas Bagci, Jayaram K. Udupa, Daniel J. Mollura
      Pages 15-24
    4. Kuangyu Shi, Xiaoyin Cheng, Nassir Navab, Stefan Foerster, Sibylle I. Ziegler
      Pages 25-33
    5. Nicholas Dowson, Paul Thomas, Jye Smith, Olivier Salvado, Stephen Rose
      Pages 35-42
    6. Shadi Albarqouni, Tobias Lasser, Weaam Alkhaldi, Ashraf Al-Amoudi, Nassir Navab
      Pages 43-51
    7. Alexandre Bousse, Jieqing Jiao, Kris Thielemans, David Atkinson, Simon Arridge, Sébastien Ourselin et al.
      Pages 53-62
    8. Joaquin L. Herraiz, Angel Torrado-Carvajal, Juan A. Hernandez-Tamames, Norberto Malpica
      Pages 63-69
    9. Jingjia Xu, Huafeng Liu, Pengcheng Shi, Fei Gao
      Pages 71-79
    10. Xiaoyin Cheng, Jun Liu, Jakob Vogel, Zhen Liu, Nassir Navab, Sibylle Ziegler et al.
      Pages 81-89
  3. Clinical Applications

    1. Front Matter
      Pages 91-91
    2. Stefano Pedemonte, Ciprian Catana, Koen Van Leemput
      Pages 93-101
    3. Hongmei Mi, Caroline Petitjean, Pierre Vera, Su Ruan
      Pages 103-112
    4. Zhiyong Xie, Aijun Zhu, Laigao Chen, Timothy McCarthy
      Pages 113-122
    5. David S. Wack, Feyza Erenler, Robert Miletich
      Pages 149-156
    6. Xiaoyan Shen, Zhiliang Liu, Zhenghui Hu, Huafeng Liu
      Pages 157-196

About this book

Introduction

This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to:
• Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities
• Molecular Imaging Enhancement
• Data Analysis of Clinical & Pre-clinical Molecular Imaging
• Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.)
• Machine Learning and Data Mining in Molecular Imaging.

Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization.

This work will bring readers from academia and industry up to date on the most recent developments in this field.

Keywords

Clinical Application Computational Methods Functional Imaging Kinetic Analysis, Dynamic Imaging, Image Reconstruction Mathematical Modeling Molecular Imaging Positron Emission Tomography (PET)

Editors and affiliations

  • Fei Gao
    • 1
  • Kuangyu Shi
    • 2
  • Shuo Li
    • 3
  1. 1.Siemens Medical SolutionsKnoxvilleUSA
  2. 2.Department of Radiotherapy and RadiooncologyTechnical University of MunichMünchenGermany
  3. 3.GE Healthcare and University of Western OntarioLondonCanada

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-18431-9
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-18430-2
  • Online ISBN 978-3-319-18431-9
  • Series Print ISSN 2212-9391
  • Series Online ISSN 2212-9413
  • About this book
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