Gengsheng Lawrence Zeng

Medical Image Reconstruction (eBook, PDF)

From Analytical and Iterative Methods to Machine Learning

• Format: PDF

Produktbeschreibung

This textbook introduces the essential concepts of tomography in the field of medical imaging. The medical imaging modalities include x-ray CT (computed tomography), PET (positron emission tomography), SPECT (single photon emission tomography) and MRI. In these modalities, the measurements are not in the image domain and the conversion from the measurements to the images is referred to as the image reconstruction.

The work covers various image reconstruction methods, ranging from the classic analytical inversion methods to the optimization-based iterative image reconstruction methods. As machine learning methods have lately exhibited astonishing potentials in various areas including medical imaging the author devotes one chapter to applications of machine learning in image reconstruction.

Based on college level in mathematics, physics, and engineering the textbook supports students in understanding the concepts. It is an essential reference for graduate students and engineers with electrical engineering and biomedical background due to its didactical structure and the balanced combination of methodologies and applications,

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Produktdetails

• Verlag: De Gruyter
• Seitenzahl: 287
• Erscheinungstermin: 4. Juli 2023
• Englisch
• ISBN-13: 9783111055404
• Artikelnr.: 70390704

Autorenporträt

Larry Zeng, Ph.D. (in Electrical Engineering, University of New Mexico), Professor of Computer Science, Utah Valley University; Adjunct Professor of Radiology and Imaging Sciences, University of Utah Valley University; IEEE Fellow;

_Main research focus: Medical Image Reconstruction.

_Recent First-Authored Peer-Reviewed Papers:

__An extended Bayesian-FBP algorithm, IEEE Trans. Nucl. Sci.

__Noise-weighted FBP algorithm for uniformly attenuated SPECT projections, IEEE Trans. Nucl. Sci.

__Noise weighting with an exponent for transmission CT, Biomedical Physics & Engineering Express.

__Does noise weighting matter in CT iterative reconstruction? IEEE Transactions on Radiation and Plasma Medical Sciences.

__A fast method to emulate an iterative POCS image reconstruction algorithm, Med. Phys.

__Fourier-domain analysis of the iterative Landweber algorithm, IEEE Transactions on Radiation and Plasma Medical Sciences.

__Estimation of the initial image's contributions to the iterative Landweber reconstruction, IEEE Transactions on Radiation and Plasma Medical Sciences.

__Maximum-likelihood expectation-maximization algorithm vs. windowed filtered backprojection algorithm: A case study, Journal of Nuclear Medicine Technology.

__Filtered backprojection implementation of the immediately-after-backprojection filtering, Biomedical Physics & Engineering Express.

__Emission expectation-maximization look-alike algorithms for x-ray CT and other applications, Medical Physics.

__Estimation of the optimal iteration number for minimal image discrepancy, IEEE Transactions on Radiation and Plasma Medical Sciences.

__Image noise covariance can be adjusted by a noise weighted filtered backprojection algorithm, IEEE Transactions on Radiation and Plasma Medical Sciences.

__Modification of Green's one-step-late algorithm for attenuated emission data, Biomed. Phys. Eng. Express.

__Counter examples for unmatched projector/backprojector in an iterative algorithm, Chinese Journal of Academic Radiology.

__Real-time selection of iteration number, Biomedical Physics & Engineering Express.

__Extension of emission expectation maximization lookalike algorithms to Bayesian algorithms, Visual Computing for Industry, Biomedicine, and Art.

__Sparse-view tomography via displacement function interpolation, Visual Computing for Industry, Biomedicine, and Art.

__Time-of-flight PET reconstruction: Two-dimensional case, Visual Computing for Industry, Biomedicine, and Art.

__Time-of-flight PET reconstruction: Three-dimensional case, Visual Computing for Industry, Biomedicine, and Art.

__Non-iterative image reconstruction from sparse magnetic resonance imaging radial data without priors, Visual Computing for Industry, Biomedicine, and Art.

__Poisson-noise weighted filter for time-of-flight positron emission tomography, Visual Computing for Industry, Biomedicine, and Art.

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__Projection-domain iteration to estimate unreliable measurements. Visual Computing for Industry, Biomedicine, and Art.

__Iterative versus non-iterative image reconstruction methods for sparse MRI, Journal of Radiology and Imaging.

__Fast filtered back projection algorithm for low-dose computed tomography, Journal of Radiology and Imaging.

__One-view time-of-flight positron emission tomography, IEEE Trans. Radiation and Plasma Medical Sciences.

__Analytic continuation and incomplete data tomography, Journal of Radiology and Imaging.

__Reducing metal artifacts by restricting negative pixels, Visual Computing for Industry, Biomedicine, and Art.

__A deep-network piecewise linear approximation formula, IEEE Access.

__A projection-domain iterative algorithm for metal artifact reduction by minimizing the total-variation norm and the negative-pixel energy, Visual Computing for Industry, Biomedicine, and Art.

__Iterative analytic extension in tomographic imaging, Visual Computing for Industry, Biomedicine, and Art.

__Photon starvation artifact reduction by shift-variant processing, IEEE Access.

__Development of a solvability map, Medical Research Archives.

__Directly filtering the sparse-view CT images by BM3D, SL Clinical Medicine: Research.

__Filtered back-projection reconstruction with non-uniformly under-sampled projections, Archives in Biomedical Engineering & Biotechnology.

Rezensionen

"The care, clarity and depth of most of the chapters contained in that book are admirable. I highly recommend this book as a source for graduates and engineers involved in the field of medical imaging." Optics and Photonics News, https://www.optica-opn.org/home/book_reviews/2023/1123/medical_image_reconstruction_radiation_from_analyt/ (01.12.2023)

For the 1rst edition:

"The structure and exposition are very good. Each chapter has a one-page summary that really does capture all the key points of the chapter. There are good explanations of all the scanning methods and how the physics works and how they are implemented. The book gives several alternate algorithms for processing the data, and gives good explanations of their strengths and weaknesses." MAA Reviews