D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 38 Citations 6,259 173 World Ranking 2845 National Ranking 1136

Overview

What is he best known for?

The fields of study he is best known for:

  • Quantum mechanics
  • Artificial intelligence
  • Optics

Guang-Hong Chen mainly focuses on Iterative reconstruction, Nuclear medicine, Imaging phantom, Artificial intelligence and Computer vision. His Iterative reconstruction study integrates concerns from other disciplines, such as Image resolution, Radiographic Image Enhancement, Medical imaging, Tomography and Compressed sensing. Within one scientific family, he focuses on topics pertaining to Projection under Medical imaging, and may sometimes address concerns connected to Data compression and Nyquist–Shannon sampling theorem.

Guang-Hong Chen combines subjects such as Image noise, Radiology and Biomedical engineering with his study of Nuclear medicine. Guang-Hong Chen focuses mostly in the field of Imaging phantom, narrowing it down to matters related to Interferometry and, in some cases, Image sensor, Refraction, Scattering and Small-angle scattering. His work on Contrast as part of his general Computer vision study is frequently connected to Tomosynthesis and Subtraction, thereby bridging the divide between different branches of science.

His most cited work include:

  • Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets. (921 citations)
  • Abdominal CT With Model-Based Iterative Reconstruction (MBIR): Initial Results of a Prospective Trial Comparing Ultralow-Dose With Standard-Dose Imaging (248 citations)
  • Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms (240 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Iterative reconstruction, Computer vision, Optics and Imaging phantom. Many of his studies on Artificial intelligence involve topics that are commonly interrelated, such as Pattern recognition. His research integrates issues of Image quality, Nuclear medicine, Image restoration, Computed tomography and Compressed sensing in his study of Iterative reconstruction.

His work deals with themes such as Tomography and Undersampling, which intersect with Compressed sensing. His work carried out in the field of Computer vision brings together such families of science as Temporal resolution and Cone beam computed tomography. Guang-Hong Chen interconnects Image resolution, Noise and Image processing in the investigation of issues within Imaging phantom.

He most often published in these fields:

  • Artificial intelligence (42.24%)
  • Iterative reconstruction (38.99%)
  • Computer vision (36.46%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (42.24%)
  • Imaging phantom (20.94%)
  • Computer vision (36.46%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Artificial intelligence, Imaging phantom, Computer vision, Iterative reconstruction and Image quality. His work in Artificial intelligence addresses subjects such as Angiography, which are connected to disciplines such as Temporal resolution and Motion artifacts. The concepts of his Imaging phantom study are interwoven with issues in Image resolution, Anisotropic diffusion, Biomedical engineering and Hounsfield scale.

His Computer vision study combines topics from a wide range of disciplines, such as Reduction and Computed tomography. His Iterative reconstruction research is multidisciplinary, relying on both Nuclear medicine and Compressed sensing. His Image quality research is multidisciplinary, incorporating elements of Noise, Perfusion scanning, Noise, Algorithm and Noise reduction.

Between 2015 and 2021, his most popular works were:

  • Accuracy of Liver Fat Quantification With Advanced CT, MRI, and Ultrasound Techniques: Prospective Comparison With MR Spectroscopy. (87 citations)
  • Learning to Reconstruct Computed Tomography Images Directly From Sinogram Data Under A Variety of Data Acquisition Conditions (38 citations)
  • Prospective Evaluation of Reduced Dose Computed Tomography for the Detection of Low-Contrast Liver Lesions: Direct Comparison with Concurrent Standard Dose Imaging (19 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Quantum mechanics
  • Optics

His primary areas of investigation include Nuclear medicine, Artificial intelligence, Optics, Imaging phantom and Iterative reconstruction. The Nuclear medicine study combines topics in areas such as Radiology and Medical imaging. His Artificial intelligence research includes themes of Angiography, Radiography, Computer vision and Pattern recognition.

Guang-Hong Chen does research in Computer vision, focusing on Projection specifically. His Imaging phantom research incorporates themes from Image quality, Anisotropic diffusion, Filter and Noise. His Iterative reconstruction study incorporates themes from Artifact, Kernel and Contrast.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Prior image constrained compressed sensing (PICCS): a method to accurately reconstruct dynamic CT images from highly undersampled projection data sets.

Guang Hong Chen;Jie Tang;Shuai Leng.
Medical Physics (2008)

1140 Citations

Abdominal CT With Model-Based Iterative Reconstruction (MBIR): Initial Results of a Prospective Trial Comparing Ultralow-Dose With Standard-Dose Imaging

Perry J. Pickhardt;Meghan G. Lubner;David H. Kim;Jie Tang.
American Journal of Roentgenology (2012)

332 Citations

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

Jie Tang;Brian E Nett;Guang-Hong Chen.
Physics in Medicine and Biology (2009)

327 Citations

Achieving routine submillisievert CT scanning: report from the summit on management of radiation dose in CT.

Cynthia H. McCollough;Guang Hong Chen;Willi Kalender;Shuai Leng.
Radiology (2012)

288 Citations

High temporal resolution and streak-free four-dimensional cone-beam computed tomography

Shuai Leng;Jie Tang;Joseph Zambelli;Brian Nett.
Physics in Medicine and Biology (2008)

186 Citations

The prototype high-resolution Fly's Eye cosmic ray detector

T Abu-Zayyad;M Al-Seady;K Belov;D.J Bird.
Nuclear Instruments & Methods in Physics Research Section A-accelerators Spectrometers Detectors and Associated Equipment (2000)

184 Citations

Fan-beam and cone-beam image reconstruction via filtering the backprojection image of differentiated projection data.

Tingliang Zhuang;Shuai Leng;Brian E. Nett;Guang Hong Chen.
Physics in Medicine and Biology (2004)

142 Citations

Streaking artifacts reduction in four-dimensional cone-beam computed tomography

Shuai Leng;Joseph Zambelli;Ranjini Tolakanahalli;Brian Nett.
Medical Physics (2008)

134 Citations

Prior image constrained compressed sensing: Implementation and performance evaluation

Pascal Thériault Lauzier;Jie Tang;Guang-Hong Chen.
Medical Physics (2011)

127 Citations

Exchange-induced enhancement of spin-orbit coupling in two-dimensional electronic systems

Guang-Hong Chen;M. E. Raikh.
Physical Review B (1999)

126 Citations

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Best Scientists Citing Guang-Hong Chen

Ge Wang

Ge Wang

Rensselaer Polytechnic Institute

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Hengyong Yu

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Xiaochuan Pan

Xiaochuan Pan

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Emil Y. Sidky

Emil Y. Sidky

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Jeffrey H. Siewerdsen

Jeffrey H. Siewerdsen

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The University of Texas MD Anderson Cancer Center

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Cynthia H. McCollough

Cynthia H. McCollough

Mayo Clinic

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Ehsan Samei

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Duke University

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Steve B Jiang

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Xun Jia

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Jiang Hsieh

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Lei Xing

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Stanford University

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Andreas Maier

Andreas Maier

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Joel G. Fletcher

Joel G. Fletcher

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