World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
33
Citations
5396
World Ranking
12575
National Ranking
798

Overview

Andrew J. Reader is affiliated with King's College London in the United Kingdom. Their research primarily focuses on the intersection of medicine and engineering, with a strong emphasis on medical imaging and related technologies.

Their main fields of study include:

  • Medicine
  • Engineering

Within these disciplines, their work concentrates on several subfields such as:

  • Radiology, Nuclear Medicine and Imaging
  • Biomedical Engineering
  • Radiation
  • Molecular Biology
  • Pulmonary and Respiratory Medicine

The key topics covered in their body of work include:

  • Medical Imaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • Radiomics and Machine Learning in Medical Imaging
  • Advanced X-ray and CT Imaging
  • Radiation Detection and Scintillator Technologies
  • Nuclear Physics and Applications
  • Advanced Radiotherapy Techniques

Andrew J. Reader has contributed to various publications, with a notable number appearing in the following frequent venues:

  • IEEE Transactions on Radiation and Plasma Medical Sciences
  • 2021 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
  • arXiv (Cornell University)
  • Radiological Physics and Technology
  • Medical Physics

Their recent published papers include:

  • Deep Learning for PET Image Reconstruction, 2020, IEEE Transactions on Radiation and Plasma Medical Sciences
  • AI for PET image reconstruction, 2023, British Journal of Radiology
  • Deep learning-based PET image denoising and reconstruction: a review, 2024, Radiological Physics and Technology

Andrew J. Reader frequently collaborates with several co-authors across their research projects. Notable collaborators include:

  • Alexander Hammers
  • Paul Marsden
  • Radhouène Neji
  • Andrew P. King
  • Sam Ellis

The researcher's contributions span significant advancements in positron emission tomography (PET) image reconstruction methods, particularly leveraging deep learning techniques and machine learning models. This work supports enhanced imaging quality and robustness in medical scanning technologies.

Best Publications

  • List-mode-based reconstruction for respiratory motion correction in PET using non-rigid body transformations

    F Lamare;F Lamare;M J Ledesma Carbayo;T Cresson;G Kontaxakis

  • Impact of image-space resolution modeling for studies with the high-resolution research tomograph.

    Florent C. Sureau;Andrew J. Reader;Claude Comtat;Claire Leroy

  • One-pass list-mode EM algorithm for high-resolution 3-D PET image reconstruction into large arrays

    A.J. Reader;S. Ally;F. Bakatselos;R. Manavaki

  • EM algorithm system modeling by image-space techniques for PET reconstruction

    A.J. Reader;P.J. Julyan;H. Williams;D.L. Hastings

  • Fast accurate iterative reconstruction for low-statistics positron volume imaging

    Andrew Reader;K. Erlandsson;M. A. Flower;R. J. Ott

  • Deep Learning for PET Image Reconstruction

    Andrew J. Reader;Guillaume Corda;Abolfazl Mehranian;Casper da Costa-Luis

  • Advances in PET Image Reconstruction

    Andrew J. Reader;Habib Zaidi

  • Where in-vivo imaging meets cytoarchitectonics: The relationship between cortical thickness and neuronal density measured with high-resolution [18F]flumazenil-PET

    Christian la Fougère;Sarah Grant;Alexey Kostikov;Ralf Schirrmacher

  • Respiratory motion correction for PET oncology applications using affine transformation of list mode data

    F Lamare;T Cresson;J Savean;C Cheze Le Rest

  • Performance Evaluation of the 32-Module quadHIDAC Small-Animal PET Scanner

    Klaus P. Schäfers;Andrew J. Reader;Michael Kriens;Christof Knoess

  • Statistical list-mode image reconstruction for the high resolution research tomograph

    A. Rahmim;M. Lenox;Andrew J. Reader;Christian Michel

  • Joint estimation of dynamic PET images and temporal basis functions using fully 4D ML-EM

    Andrew J Reader;Florent C Sureau;Claude Comtat;Régine Trébossen

  • 4D image reconstruction for emission tomography

    Andrew J Reader;Jeroen Verhaeghe

  • Model-Based Deep Learning PET Image Reconstruction Using Forward–Backward Splitting Expectation–Maximization

    Abolfazl Mehranian;Andrew J. Reader

  • Fast ray-tracing technique to calculate line integral paths in voxel arrays

    Huaxia Zhao;A.J. Reader

  • Characterization of age/sex and the regional distribution of mGluR5 availability in the healthy human brain measured by high-resolution [(11)C]ABP688 PET.

    Jonathan M. DuBois;Olivier G. Rousset;Jared Rowley;Manuel Porras-Betancourt

  • MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

    Philip Novosad;Andrew J Reader;Andrew J Reader

  • Fully 4D image reconstruction by estimation of an input function and spectral coefficients

    A. J. Reader;J.C. Matthews;F.C. Sureau;C. Comtat

  • Regularized one-pass list-mode EM algorithm for high resolution 3D PET image reconstruction into large arrays

    A.J. Reader;S. Ally;F. Bakatselos;R. Manavaki

  • Intercomparison of four reconstruction techniques for positron volume imaging with rotating planar detectors

    Andrew Reader;D. Visvikis;K. Erlandsson;R. J. Ott

  • Direct reconstruction of parametric images using any spatiotemporal 4D image based model and maximum likelihood expectation maximisation

    Julian C. Matthews;Georgios I. Angelis;Fotis A. Kotasidis;Pawel J. Markiewicz

  • MR-Guided Kernel EM Reconstruction for Reduced Dose PET Imaging

    James Bland;Abolfazl Mehranian;Martin A. Belzunce;Sam Ellis

Frequent Co-Authors

Claudia Prieto
Claudia Prieto Pontificia Universidad Católica de Chile
William R B Lionheart
William R B Lionheart University of Manchester
Alexander Hammers
Alexander Hammers King's College London
Jean-Paul Soucy
Jean-Paul Soucy Montreal Neurological Institute and Hospital
Andrew P. King
Andrew P. King King's College London
Georg Northoff
Georg Northoff University of Ottawa
Pedro Rosa-Neto
Pedro Rosa-Neto McGill University
Alain Dagher
Alain Dagher Montreal Neurological Institute and Hospital
Julia A. Schnabel
Julia A. Schnabel King's College London
Marco Leyton
Marco Leyton McGill University

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