Xray computed tomography ct has experienced tremendous growth in recent years, in terms of both basic technology and new clinical applications. Medical image reconstruction a conceptual tutorial gengsheng. Evolution and innovation in ct image reconstruction are often driven by advances in ct system designs, which in turn are driven by clinical demands. It covers topics in twodimensional 2d parallelbeam and fanbeam imaging, threedimensional 3d parallel ray, parallel plane, and conebeam imaging. Image reconstruction methods are central to many of the new applications of medical imaging. These techniques are the authors most recent research results. The reconstruction process is based on use of an algorithm that uses the attenuation data measured by detectors to systematically build up the image for viewing. Image reconstruction for fewview computed tomography based. Ct image is a product of complex calculation based on backprojection reconstruction algorithm. Lowdose ct image reconstruction has been a popular research topic in recent years. A very general block diagram for image reconstruction problems is the following.
The ct image is not a real shade like in classical radiography, but a picture which represents with some probability 95% the similarity between the real object and its calculated ct image. Image reconstruction in ct is a mathematical process that generates tomographic images from xray projection data acquired at many different angles around the patient. The first type tended to be analytical methods, such as filtered backprojection fbp for xray computed tomography ct and the inverse fourier transform for magnetic resonance imaging mri, based on simple mathematical models for the imaging systems. This book is an attempt to bring together in one place many of the key ingredients.
A ct reconstruction approach from sparse pr ojection with adaptiveweighted diagonal totalvariation s1692 ct image reconstruction, journal of xray science and t echnology 21 20, 161176. Mar 04, 2019 image reconstruction image reconstruction is a mathematical process that generates tomographic images from xray projection data acquired at many different angles around the patient. Image reconstruction definition of image reconstruction by. Since the fourier transform plays a major role in the understanding of ct reconstruction, we introduce it here to define the appropriate terms.
The traditional total variation tv minimization algorithm is an image reconstruction algorithm based on compressed sensing, which can accurately reconstruct images from sparse data or highly noisy data and has been widely used in lowdose computed tomography ct. This book presents both analytical and iterative methods of these technologies and their applications in xray ct computed tomography, spect single photon. In this paper, we integrate a convolutional neural network cnn into the computed tomography ct image reconstruction process. This book introduces the classical and modern image reconstruction technologies. The algorithmic development can generally be classified into three major areas. Computed tomography image reconstruction presented by. An introduction to reconstruction methods in helical and multislice ct can be found in hsiehs book 3. In medical imaging, deep learning has been primarily used for image processing and analysis. This theorem states that the 1d ft of the projection. An mri term for the mathematical process of converting the composite signals obtained during the data acquisition phase into an image.
A typical reconstruction method based on postlog measurements is calle spultra. 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. The field of medical image reconstruction has seen roughly four types of methods. A ct scan, or computed tomography scan is a medical imaging procedure that uses computerprocessed combinations of many xray measurements taken from different angles to produce crosssectional images of specific areas of a scanned object, allowing the user to see inside the object without cutting.
A new cbct reconstruction algorithm, iterative cbct, has recently been introduced into the truebeam system, and combines the 2 image reconstruction approaches mentioned previously. The technology advanced intelligent cleariq engine. Image display is examined from traditional methods through the most recent advancments. Recent advances in ct image reconstruction springerlink. Iterative reconstruction 101 imaging technology news. This is usually done by a computer with the assistance of some mathematical formulas.
Ct computed tomography scans a level physics youtube. An image pattern approach cranial neuroimaging and clinical neuroanatomy. The 1979 nobel prize in physiology or medicine was awarded jointly to south african american physicist allan m. Deep learning methods to guide ct image reconstruction and. Mar 16, 2020 computed tomography ct reconstruction is a medical imaging technique where a series of slices, or individual images of the inside of the body, are stacked and correlated with each other to create a meaningful diagnostic image. The last chapter of the book is devoted to the techniques of using a fast analytical algorithm to reconstruct an image that is equivalent to an iterative reconstruction. For image reconstruction from fewview projection data, m is much less than n, thus, it is difficult to obtain accurate ct image with the underdetermined eq. Basic principles of computed tomography physics and technical considerations kyongtae t. Helical ct is much faster than stepandshoot and is the standard method used in ct in the modern era. Ct artifacts are common and can occur for various reasons. This tutorial has been developed by dr tarun mittal, cardiac. Synopsis of image reconstruction this book treats image reconstruction as an inverse problem of the following form. Statistical iterative reconstruction for xray computed tomography.
Whiting introduction slightly more than three decades old, computed tomography ct continues to advance rapidly in both imaging performance and widening clinical applications. When ct was developed by godfrey hounsfield in the 1970s, the original reconstruction algorithm he used was iterative reconstruction ir, where the software builds an image and then revises it with scores of reiterations to. The primary focus of this book is on statistical methods for tomographic image reconstruction using reasonably realistic physical models. This tutorial takes you through the concepts of ct image display including windowing and different types of image reconstructions. Oct 22, 2019 canon medical systems usa announced the fda granted 501k clearance to its image reconstruction technology that uses a deep learning algorithm. Even more importantly, a contrast resolution could be achieved that for the first time in radiology permitted the differentiation of soft tissue inside the highly attenuating skull. Magnetic resonance imaging and computed tomography spine. Improvements in cbct image quality using a novel iterative. Basic principles of ct scanners and image reconstruction.
Filtered backprojection is the standard method of ct reconstruction. This book presents both analytical and iterative methods of these technologies and their applications in xray ct computed. Kak and malcolm slaney, principles of computerized tomographic imaging, society of industrial and applied mathematics, 2001 electronic copy each chapter of this book is available as an adobe pdf file. For flexible tomographic reconstruction, open source toolboxes are available, such as pyronn, tomopy, conrad, odl, the astra toolbox, and tigre. Over the past two decades, rapid system and hardware development of xray computed tomography ct technologies has been accompanied by equally exciting advances in image reconstruction algorithms. Pdf a ct reconstruction approach from sparse projection. Pdf computed tomography download full pdf book download. Image reconstruction in circular conebeam computed tomography by constrained, totalvariation minimization. Jan 16, 20 over the past two decades, rapid system and hardware development of xray computed tomography ct technologies has been accompanied by equally exciting advances in image reconstruction algorithms. Computed tomography ct was the first noninvasive radiological method allowing the generation of tomographic images of every part of the human body without superimposition of adjacent structures. This course will provide an introduction these techniques in a consistent framework by developing a sequence of software tools for the reconstruction of medical imaging data. Knowledge of these artifacts is important because they can mimic pathology e. Both analytical and iterative methods are presented. This book is intended for students, engineers, and researchers who are interested in medical image reconstruction.
Tomopy is an opensource python toolbox to perform tomographic data processing and image reconstruction tasks at the advanced photon source at argonne national laboratory. Changing the filter yields a tradeoff between noise and sharpness of the image. A conceptual tutorial introduces the classical and modern image reconstruction technologies, such as twodimensional 2d parallelbeam and fanbeam imaging, threedimensional 3d parallel ray, parallel plane, and conebeam imaging. Learn vocabulary, terms, and more with flashcards, games, and other study tools. A basic description of the mechanism of ct computed tomography scans for medical use in remote sensing. From a historical perspective, for example, the fanbeam axial. A ct scan, or computed tomography scan is a medical imaging procedure that uses computerprocessed combinations of many xray measurements taken from different angles to produce crosssectional tomographic images virtual slices of specific areas of a scanned object, allowing the user to see inside the object without cutting. Image reconstruction has fundamental impacts on image quality and therefore on radiation dose. Kak and malcolm slaney, principles of computerized tomographic imaging, ieee press, 1988. This book provides an overview of the evolution of ct, the mathematical and physical aspects of the technology, and the fundamentals of image reconstruction using algorithms. Image reconstruction in circular conebeam computed.
Tabakov, 1999 oct 24, 2017 this tutorial takes you through the concepts of ct image display including windowing and different types of image reconstructions. Basic principles of computed tomography physics and technical. Pivotal to understanding of ct reconstruction relates 2d ft of image to 1d ft of its projection n. It covers the fundamentals of computerized tomography, including all the computational and mathematical procedures underlying data collection, image reconstruction and image display. The rapid evolution of mathematical methods of image reconstruction in computed tomography ct reflects the race to produce an efficient yet accurate image reconstruction method while keeping radiation dose to a minimum and has defined improveme. Provides an overview of the evolution of ct, the mathematical and physical aspects of the technology, and the fundamentals of image reconstruction using algorithms. Image reconstruction ct radiology reference article. Computed tomographyctis a widely used imaging technique in medical. Study of ct image reconstruction algorithm based on high.
May 21, 2012 a basic description of the mechanism of ct computed tomography scans for medical use in remote sensing. A ct reconstruction approach from sparse projection with adaptiveweighted diagonal totalvariation in biomedical application. Although focused on pet, spect, xray ct, and mri, tomographic. For example, in emission tomography, f represents the 3d spatial distribution of a radiotracer.
This book studied the performance of the leading reconstruction methods from both. Nevertheless, analytical image reconstruction methods, even though based on somewhat unrealistic simpli. Jul 23, 20 ct images are created from data and a computer uses software to reconstruct this data into a diagnosticquality image. Mar 09, 2017 the rapidlyrising field of machine learning, including deep learning, has inspired applications across many disciplines. Analytical tomographic image reconstruction methods. Fessler university of michigan preface this book describes the theory and practice of iterative methods for tomographic image reconstruction and related inverse problems such as image restoration. Xray computed tomography mathematics and physics of. Aibased ct image reconstruction technology receives fda.
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