Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications

Themis P. Exarchos (University of Ioannina, Greece ), Athanasios Papadopoulos (University of Ioannina, Greece ) and Dimitrios I. Fotiadis (University of Ioannina, Greece )
Indexed In: SCOPUS
Release Date: April, 2009|Copyright: © 2009 |Pages: 598
ISBN13: 9781605663142|ISBN10: 160566314X|EISBN13: 9781605663159|DOI: 10.4018/978-1-60566-314-2


Biomedical imaging enables physicians to evaluate areas of the body not normally visible, helping to diagnose and examine disease in patients.

The Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications includes recent state-of-the-art methodologies that introduce biomedical imaging in decision support systems and their applications in clinical practice. This Handbook of Research provides readers with an overview of the emerging field of image-guided medical and biological decision support, bringing together various research studies and highlighting future trends.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Biomedical Applications
  • Biomedical functional infrared imaging
  • Cardiac magnetic resonance imaging
  • Combining geometry and image in biomedical systems
  • Computer-aided diagnosis in breast imaging
  • Decision support in biomedicine
  • Developments in intracoronary ultrasound processing
  • Diagnostic Imaging
  • Diagnostic support systems and computational intelligence
  • Facial expression recognition
  • Image processing and machine learning techniques
  • Imaging and clinical data for decision support
  • Randomness in fMRI

Reviews and Testimonials

This handbook features the most current research findings in all aspects of biomedical imaging, diagnostic and decision support methodologies, from theoretical and algorithmic problems to successfully designed and developed biomedical image guided decision support systems.

– T. P. Exarchos, A. Papadopoulos and D. I. Fotiadis, University of Ioannina, Greece

It presents current international research findings in biomedical imaging and in diagnostic and decision support methodologies, with coverage ranging from theoretical and algorithmic problems to successful biomedical image-guided, decision-support systems.

– Book News Inc. (June 2009)

Table of Contents and List of Contributors

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Diagnostic imaging in biomedicine is based on several techniques and processes aiming at the enhancement of experts’ capability to evaluate imaging data. Diagnostic imaging combines image processing and decision support methods to improve and accelerate case-specific advice in clinical environments.

Decision support today focuses on diagnosis, prognosis, therapy and follow-up recommendations and is usually based on simple and easily acquired features met in biomedical data. The latest breakthroughs in imaging technologies in medicine lead to an explosion of the imaging data available. New techniques and methods addressing mainly acquisition and processing of information from medical and biological images appeared and the integration of biomedical image data into decision support systems is a challenging task. This mainly supports the decision on the patient’s health status and the quality of the extracted diagnosis and prognosis.

Despite the wide application of decision support systems in medicine, only a few such systems have been developed for biomedical imaging. One of the reasons is the difficulty in representing anatomical or functional units of the images in formal features. Dealing with this uncertain and imprecise information increases the complexity of decision support systems. Furthermore, each imaging modality and each type of pathology requires the development of dedicated low-level feature extractors. Although, standard computer-vision techniques may be used (template matching, region growing, etc.), specific methodologies and algorithmic approaches need to be developed. These difficulties, combined with the computational cost associated with biomedical imaging applications, have prevented, so far, the development of fully automated image guided decision support systems. By producing a formal and structured representation of the images, imaging decision support systems enable new applications such as the automated generation of anatomical and functional atlases or the content-driven image retrieval. The abundance of information derived from cross-sectional imaging modalities, such as computed tomography (CT), magnetic resonance imaging (MRI), single photon emission computerized tomography (SPECT), positron emission tomography (PET), or conventional planar imaging technologies such as digital X-ray, and ultrasound highlights the need for the design and the development of decision support systems based mainly on multiple imaging data. Such tools improve diagnostic accuracy and overall reproducibility by providing a second opinion and objective measurements of normal and abnormal patterns.

This handbook features the most current research findings in all aspects of biomedical imaging, diagnostic and decision support methodologies, from theoretical and algorithmic problems to successfully designed and developed biomedical image guided decision support systems. The handbook is intended for all those working in the field of medical image analysis and information technologies in biomedicine. It provides different approaches and levels of knowledge for experienced researchers, graduate students, computer engineers, and medical practitioners interested in emerging intelligent diagnostic tools and systems. The handbook serves as the basis for understanding the future of decision support technologies and services based on biomedical imaging, exemplifying the impact of knowledge extraction on clinical environments.

The objective of this Handbook is to present state of the art in the field and present advances which:

  • Bridge the gap between medical and biological imaging with clinical decision support systems.
  • Integrate biomedical images in the most efficient way in existing decision support systems.
  • Present a unified framework for image analysis in medical and biological applications.
  • Enhance the readers’ capability in designing decision support systems which employ biomedical images.

    This book is divided into three sections. The first introduces the readers to some advanced image-based decision support applications. This part addresses the utilization of existing methodologies and techniques to several clinical areas with increased needs for computer-aided assistance. An overview of computational methods and tools applied in decision support systems is presented. Integration of imaging data as well as new approaches on cardiac, intracoronary and cardiac MRI data are analyzed extensively. In addition, clinical decision support systems for the interpretation of hepatic lesions, oncology samples and breast imaging are presented, along with a quantitative analysis of hysteroscopy imaging in gynecological cancer. The second section of the book presents novel methodologies in the field of biomedical imaging. 3D quantitative radionuclide dosimetry and combination of geometry and image data appear to have great interest in the area of radiation therapy. Diffusion tensor imaging, infrared imaging as well as DNA microarray analysis are new issues. Research studies based on the mechano-elastic properties of matter and elastographic applications are also presented. In the third section, methodological approaches of image processing and their medical applications are presented

    Author(s)/Editor(s) Biography

    Themis P. Exarchos was born in Ioannina, Greece (1980). He received the Diploma Degree in Computer Engineer¬ing and Informatics from the Engineering School of the University of Patras (2003). He received the PhD degree from the University of Ioannina (2009); his PhD thesis is entitled “Data Mining and Healthcare Decision Support System.” He is a member of the Unit of Medical Technology and Intelligent Information Systems at the University of Ioannina, working in Research and Technology Development projects. His research interests include data mining, decision support systems in healthcare, biomedical applications including biomedical imaging and bioinformatics. Dr. Exarchos is the author of more than fifty papers in scientific journals and conference proceedings.
    Athanasios Papadopoulos received his degree in Physics from the Department of Physics of the University of Patras (1994). He completed his MSc in Medical Physics at University of Surrey (UK). He received his PhD from the Department of Medical Physics from University of Ioannina, Greece (2006). He is serving as a radiation physicist in the Department of Nuclear medicine of University Hospital of Ioannina, Greece. He is a member of the research group of the “Foundation for Research and Technology-Hellas / Biomedical Research Institute” and the Unit of Medical Technology and Intelligent Information Systems. His major research interests include medical image processing, medical decision support, computer-aided detection and diagnosis, machine learning and data mining. Lately his work is related to the use of vital signs of the human body, their analysis and use of intelligent methods for diagnosis or prognosis. Dr. Papadopoulos is the author of two book chapters and more than twenty papers in scientific journals and international conference proceedings.
    Dimitrios I. Fotiadis is a professor of Biomedical Engineering and the director of the Unit of Medical Technology and Intelligent Information Systems, at the Department of Materials Science Engineering, University of Ioannina. He is also an associated member of Biomedical Research Institute. He holds Diploma in Chemical Engineering from the National Technical University of Athens (1985) and a PhD in Chemical Engineering and Materials Science from the University of Minnesota, (Minneapolis, USA) (1990). He served as visiting researcher at the RWTH (Aachen, Germany) and the Massachusetts Institute of Technology (Boston, USA). He has published more than 120 papers in scientific journals, 250 papers in peer-reviewed conference proceedings, more than 20 chapters in books and he is the editor of 14 books. His work has received more than 800 citations. His research interests include modelling of human tissues and organs, intelligent wearable devices for automated diagnosis and bioinformatics. He is the chairman of the board and CEO of the Science and Technology Park of Epirus, National Representative of Greece in FP7 and he coordinates several R&D projects funded by the EC and other bodies.


    Editorial Board

  • Apostolos H. Karantanas, University Hospital, Greece
  • Peter Kokol, University of Maribor, Slovenia
  • Lena Kostaridou, University of Patras, Greece
  • Lhenka Lhotska, Czech Technical University, Czech Republic
  • Konstantinos N. Malizos, University of Thessalia, Greece
  • George Panayiotakis, University of Patras, Greece
  • Constantinos Pattichis, University of Cyprus, Cyprus