Medical Image Reconstruction -  Gengsheng Lawrence Zeng

Medical Image Reconstruction (eBook)

From Analytical and Iterative Methods to Machine Learning
eBook Download: PDF
2023 | 2. Auflage
287 Seiten
Walter de Gruyter GmbH & Co.KG (Verlag)
978-3-11-105540-4 (ISBN)
Systemvoraussetzungen
69,95 inkl. MwSt
  • Download sofort lieferbar
  • Zahlungsarten anzeigen

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,



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.

__Pre-filter that incorporates the noise model, Visual Computing for Industry, Biomedicine, and Art.

__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.

Erscheint lt. Verlag 4.7.2023
Sprache englisch
Themenwelt Mathematik / Informatik Mathematik
Medizinische Fachgebiete Radiologie / Bildgebende Verfahren Radiologie
Naturwissenschaften Physik / Astronomie
ISBN-10 3-11-105540-X / 311105540X
ISBN-13 978-3-11-105540-4 / 9783111055404
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 30,3 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich

von Marija Pinto

eBook Download (2023)
Urban & Fischer Verlag - Lehrbücher
26,99