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Iterative Reconstruction Framework for High-resolution X-ray CT Data

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Page : pages

File Size : 10,63 MB

Release : 2003

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Book Description

Small animal medical imaging has become an important tool for researchers as it allows noninvasively screening animal models for pathologies as well as monitoring disease progression and therapy response. Currently, clinical CT scanners typically use a Filtered Backprojection (FBP) based method for image reconstruction. This algorithm is fast and generally produces acceptable results, but has several drawbacks. Firstly, it is based upon line integrals, which do not accurately describe the process of X-ray attenuation. Secondly, noise in the projection data is not properly modeled with FBP. On the other hand, iterative algorithms allow the integration of more complicated system models as well as robust scatter and noise correction techniques. Unfortunately, the iterative algorithms also have much greater computational demands than their FBP counterparts. In this thesis, we develop a framework to support iterative reconstructions of high-resolution X-ray CT data. This includes exploring various system models and algorithms as well as developing techniques to manage the significant computational and system storage requirements of the iterative algorithms. Issues related to the development of this framework as well as preliminary results are presented.



Iterative Reconstruction of Cone-beam Micro-CT Data

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Publisher :

Page : 113 pages

File Size : 39,69 MB

Release : 2006

Category : Tomography

ISBN :

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Book Description

The use of x-ray computed tomography (CT) scanners has become widespread in both clinical and preclinical contexts. CT scanners can be used to noninvasively test for anatomical anomalies as well as to diagnose and monitor disease progression. However, the data acquired by a CT scanner must be reconstructed prior to use and interpretation. A reconstruction algorithm processes the data and outputs a three dimensional image representing the x-ray attenuation properties of the scanned object. The algorithms in most widespread use today are based on filtered backprojection (FBP) methods. These algorithms are relatively fast and work well on high quality data, but cannot easily handle data with missing projections or considerable amounts of noise. On the other hand, iterative reconstruction algorithms may offer benefits in such cases, but the computational burden associated with iterative reconstructions is prohibitive. In this work, we address this computational burden and present methods that make iterative reconstruction of high-resolution CT data possible in a reasonable amount of time. Our proposed techniques include parallelization, ordered subsets, reconstruction region restriction, and a modified version of the SIRT algorithm that reduces the overall run-time. When combining all of these techniques, we can reconstruct a 512 x 512 x 1022 image from acquired micro-CT data in less than thirty minutes.



Computed Tomography

Author : Willi A. Kalender

Publisher : John Wiley & Sons

Page : 372 pages

File Size : 31,16 MB

Release : 2011-07-07

Category : Medical

ISBN : 3895786446

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Book Description

The book offers a comprehensive and user-oriented description of the theoretical and technical system fundamentals of computed tomography (CT) for a wide readership, from conventional single-slice acquisitions to volume acquisition with multi-slice and cone-beam spiral CT. It covers in detail all characteristic parameters relevant for image quality and all performance features significant for clinical application. Readers will thus be informed how to use a CT system to an optimum depending on the different diagnostic requirements. This includes a detailed discussion about the dose required and about dose measurements as well as how to reduce dose in CT. All considerations pay special attention to spiral CT and to new developments towards advanced multi-slice and cone-beam CT. For the third edition most of the contents have been updated and latest topics like dual source CT, dual energy CT, flat detector CT and interventional CT have been added. The enclosed CD-ROM again offers copies of all figures in the book and attractive case studies, including many examples from the most recent 64-slice acquisitions, and interactive exercises for image viewing and manipulation. This book is intended for all those who work daily, regularly or even only occasionally with CT: physicians, radiographers, engineers, technicians and physicists. A glossary describes all the important technical terms in alphabetical order. The enclosed DVD again offers attractive case studies, including many examples from the most recent 64-slice acquisitions, and interactive exercises for image viewing and manipulation. This book is intended for all those who work daily, regularly or even only occasionally with CT: physicians, radiographers, engineers, technicians and physicists. A glossary describes all the important technical terms in alphabetical order.



Fundamentals of Computerized Tomography

Author : Gabor T. Herman

Publisher : Springer Science & Business Media

Page : 302 pages

File Size : 15,8 MB

Release : 2009-07-14

Category : Computers

ISBN : 1846287235

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Book Description

This revised and updated second edition – now with two new chapters - is the only book to give a comprehensive overview of computer algorithms for image reconstruction. It covers the fundamentals of computerized tomography, including all the computational and mathematical procedures underlying data collection, image reconstruction and image display. Among the new topics covered are: spiral CT, fully 3D positron emission tomography, the linogram mode of backprojection, and state of the art 3D imaging results. It also includes two new chapters on comparative statistical evaluation of the 2D reconstruction algorithms and alternative approaches to image reconstruction.



Statistical Modeling and Path-based Iterative Reconstruction for X-ray Computed Tomography

Author : Meng Wu

Publisher :

Page : pages

File Size : 36,22 MB

Release : 2015

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Book Description

X-ray computed tomography (CT) and tomosynthesis systems have proven to be indispensable components in medical diagnosis and treatment. My research is to develop advanced image reconstruction and processing algorithms for the CT and tomosynthesis systems. Streak artifacts caused by metal objects such as dental fillings, surgical instruments, and orthopedic hardware may obscure important diagnostic information in X-ray computed tomography (CT) images. To improve the image quality, we proposed to complete the missing kilovoltage (kV) projection data with selectively acquired megavoltage (MV) data that do not suffer from photon starvation. We developed two statistical image reconstruction methods, dual-energy penalized weighted least squares and polychromatic maximum likelihood, for combining kV and selective MV data. Cramer-Rao Lower Bound for Compound Poisson was studied to revise the statistical model and minimize radiation dose. Numerical simulations and phantom studies have shown that the combined kV/MV imaging systems enable a better delineation of structures of interest in CT images for patients with metal objects. The x-ray tube on the CT system produces a wide x-ray spectrum. Polychromatic statistical CT reconstruction is desired for more accurate quantitative measurement of the chemical composition and density of the tissue. Polychromatic statistical reconstruction algorithms usually have very high computational demands due to complicated optimization frameworks and the large number of spectrum bins. We proposed a spectrum information compression method and a new optimization framework to significantly reduce the computational cost in reconstructions. The new algorithm applies to multi-material beam hardening correction, adaptive exposure control, and spectral imaging. Model-based iterative reconstruction (MBIR) techniques have demonstrated many advantages in X-ray CT image reconstruction. The MBIR approach is often modeled as a convex optimization problem including a data fitting function and a penalty function. The tuning parameter value that regulates the strength of the penalty function is critical for achieving good reconstruction results but is difficult to choose. We have developed two path seeking algorithms that are capable of generating a path of MBIR images with different strengths of the penalty function. The errors of the proposed path seeking algorithms are reasonably small throughout the entire reconstruction path. With the efficient path seeking algorithm, we suggested a path-based iterative reconstruction (PBIR) to obtain complete information from the scanned data and reconstruction model. Additionally, we have developed a convolution-based blur-and-add model for digital tomosynthesis systems that can be used in efficient system analysis, task-dependent optimization, and filter design. We also proposed a computationally practical algorithm to simulate and subtract out-of-plane artifacts in tomosynthesis images using patient-specific prior CT volumes.



Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine

Author : Pierre Grangeat

Publisher : Springer Science & Business Media

Page : 313 pages

File Size : 28,75 MB

Release : 2013-03-09

Category : Medical

ISBN : 9401587493

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Book Description

This book contains a selection of communications presented at the Third International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, held 4-6 July 1995 at Domaine d' Aix-Marlioz, Aix-Ies-Bains, France. This nice resort provided an inspiring environment to hold discussions and presentations on new and developing issues. Roentgen discovered X-ray radiation in 1895 and Becquerel found natural radioactivity in 1896 : a hundred years later, this conference was focused on the applications of such radiations to explore the human body. If the physics is now fully understood, 3D imaging techniques based on ionising radiations are still progressing. These techniques include 3D Radiology, 3D X-ray Computed Tomography (3D-CT), Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET). Radiology is dedicated to morphological imaging, using transmitted radiations from an external X-ray source, and nuclear medicine to functional imaging, using radiations emitted from an internal radioactive tracer. In both cases, new 3D tomographic systems will tend to use 2D detectors in order to improve the radiation detection efficiency. Taking a set of 2D acquisitions around the patient, 3D acquisitions are obtained. Then, fully 3D image reconstruction algorithms are required to recover the 3D image of the body from these projection measurements.



3D Image Reconstruction for CT and PET

Author : Daniele Panetta

Publisher : CRC Press

Page : 97 pages

File Size : 43,29 MB

Release : 2020-10-11

Category : Medical

ISBN : 100017588X

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Book Description

This is a practical guide to tomographic image reconstruction with projection data, with strong focus on Computed Tomography (CT) and Positron Emission Tomography (PET). Classic methods such as FBP, ART, SIRT, MLEM and OSEM are presented with modern and compact notation, with the main goal of guiding the reader from the comprehension of the mathematical background through a fast-route to real practice and computer implementation of the algorithms. Accompanied by example data sets, real ready-to-run Python toolsets and scripts and an overview the latest research in the field, this guide will be invaluable for graduate students and early-career researchers and scientists in medical physics and biomedical engineering who are beginners in the field of image reconstruction. A top-down guide from theory to practical implementation of PET and CT reconstruction methods, without sacrificing the rigor of mathematical background Accompanied by Python source code snippets, suggested exercises, and supplementary ready-to-run examples for readers to download from the CRC Press website Ideal for those willing to move their first steps on the real practice of image reconstruction, with modern scientific programming language and toolsets Daniele Panetta is a researcher at the Institute of Clinical Physiology of the Italian National Research Council (CNR-IFC) in Pisa. He earned his MSc degree in Physics in 2004 and specialisation diploma in Health Physics in 2008, both at the University of Pisa. From 2005 to 2007, he worked at the Department of Physics "E. Fermi" of the University of Pisa in the field of tomographic image reconstruction for small animal imaging micro-CT instrumentation. His current research at CNR-IFC has as its goal the identification of novel PET/CT imaging biomarkers for cardiovascular and metabolic diseases. In the field micro-CT imaging, his interests cover applications of three-dimensional morphometry of biosamples and scaffolds for regenerative medicine. He acts as reviewer for scientific journals in the field of Medical Imaging: Physics in Medicine and Biology, Medical Physics, Physica Medica, and others. Since 2012, he is adjunct professor in Medical Physics at the University of Pisa. Niccolò Camarlinghi is a researcher at the University of Pisa. He obtained his MSc in Physics in 2007 and his PhD in Applied Physics in 2012. He has been working in the field of Medical Physics since 2008 and his main research fields are medical image analysis and image reconstruction. He is involved in the development of clinical, pre-clinical PET and hadron therapy monitoring scanners. At the time of writing this book he was a lecturer at University of Pisa, teaching courses of life-sciences and medical physics laboratory. He regularly acts as a referee for the following journals: Medical Physics, Physics in Medicine and Biology, Transactions on Medical Imaging, Computers in Biology and Medicine, Physica Medica, EURASIP Journal on Image and Video Processing, Journal of Biomedical and Health Informatics.



Development and Implementation of Fully 3D Statistical Image Reconstruction Algorithms for Helical CT and Half-ring PET Insert System

Author : Daniel Brian Keesing

Publisher :

Page : 159 pages

File Size : 14,94 MB

Release : 2009

Category : Electronic dissertations

ISBN :

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Book Description

X-ray computed tomography (CT) and positron emission tomography (PET) have become widely used imaging modalities for screening, diagnosis, and image-guided treatment planning. Along with the increased clinical use are increased demands for high image quality with reduced ionizing radiation dose to the patient. Despite their significantly high computational cost, statistical iterative reconstruction algorithms are known to reconstruct high-quality images from noisy tomographic datasets. The overall goal of this work is to design statistical reconstruction software for clinical x-ray CT scanners, and for a novel PET system that utilizes high-resolution detectors within the field of view of a whole-body PET scanner. The complex choices involved in the development and implementation of image reconstruction algorithms are fundamentally linked to the ways in which the data is acquired, and they require detailed knowledge of the various sources of signal degradation. Both of the imaging modalities investigated in this work have their own set of challenges. However, by utilizing an underlying statistical model for the measured data, we are able to use a common framework for this class of tomographic problems. We first present the details of a new fully 3D regularized statistical reconstruction algorithm for multislice helical CT. To reduce the computation time, the algorithm was carefully parallelized by identifying and taking advantage of the specific symmetry found in helical CT. Some basic image quality measures were evaluated using measured phantom and clinical datasets, and they indicate that our algorithm achieves comparable or superior performance over the fast analytical methods considered in this work. Next, we present our fully 3D reconstruction efforts for a high-resolution half-ring PET insert. We found that this unusual geometry requires extensive redevelopment of existing reconstruction methods in PET. We redesigned the major components of the data modeling process and incorporated them into our reconstruction algorithms. The algorithms were tested using simulated Monte Carlo data and phantom data acquired by a PET insert prototype system. Overall, we have developed new, computationally efficient methods to perform fully 3D statistical reconstructions on clinically-sized datasets.



Machine Learning for Tomographic Imaging

Author : Ge Wang

Publisher : Programme: Iop Expanding Physi

Page : 250 pages

File Size : 16,82 MB

Release : 2019-12-30

Category : Technology & Engineering

ISBN : 9780750322140

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Book Description

Machine learning represents a paradigm shift in tomographic imaging, and image reconstruction is a new frontier of machine learning. This book will meet the needs of those who want to catch the wave of smart imaging. The book targets graduate students and researchers in the imaging community. Open network software, working datasets, and multimedia will be included. The first of its kind in the emerging field of deep reconstruction and deep imaging, Machine Learning for Tomographic Imaging presents the most essential elements, latest progresses and an in-depth perspective on this important topic.



Medical Imaging Systems

Author : Andreas Maier

Publisher : Springer

Page : 263 pages

File Size : 30,34 MB

Release : 2018-08-02

Category : Computers

ISBN : 3319965204

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Book Description

This open access book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are closely related to traditional camera systems such as endoscopy and microscopy. This is followed by more complex image formation processes: magnetic resonance imaging, X-ray projection imaging, computed tomography, X-ray phase-contrast imaging, nuclear imaging, ultrasound, and optical coherence tomography.