World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
52
Citations
15248
World Ranking
4987
National Ranking
300

Research.com Recognitions

  • 2016 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to computer vision and applications

Overview

Emanuele Trucco is affiliated with the University of Dundee in the United Kingdom. Their research primarily spans the field of medicine, with a considerable focus on ophthalmology and related subfields such as radiology, nuclear medicine and imaging, computer vision and pattern recognition, genetics, and molecular biology.

Their main topics of work cover several aspects of retinal health and associated conditions. Key research areas include:

  • Retinal Imaging and Analysis
  • Retinal Diseases and Treatments
  • Glaucoma and retinal disorders
  • Retinal and Optic Conditions
  • Acute Ischemic Stroke Management
  • Genetic Associations and Epidemiology
  • Medical Imaging and Analysis

Emanuele Trucco has published extensively, including work in multiple well-known venues. Frequent publication venues include:

  • Scientific Reports
  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Translational Vision Science & Technology
  • Eye

Notable recent papers authored or coauthored by Emanuele Trucco are:

  • "Using machine learning approaches for multi-omics data analysis: A review," 2021, Biotechnology Advances
  • "A foundation model for generalizable disease detection from retinal images," 2023, Nature
  • "A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification," 2020, Medical Image Analysis
  • "Retinal imaging in Alzheimer's disease," 2021, Journal of Neurology Neurosurgery & Psychiatry
  • "Retinal Optical Coherence Tomography Features Associated With Incident and Prevalent Parkinson Disease," 2023, Neurology

Emanuele Trucco has collaborated frequently with several researchers. The most common coauthors include:

  • Tom MacGillivray
  • Paul J. Foster
  • Alex S. F. Doney
  • Anthony P. Khawaja
  • Cathy Williams

Their scholarly output also includes contributions to book publications, particularly with Springer Science+Business Media. One published book is titled Imaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis (2022).

Award recognition includes being named a Fellow of the International Association for Pattern Recognition (IAPR) in 2016 for contributions to computer vision and applications.

Best Publications

  • Introductory Techniques for 3-D Computer Vision

    Emanuele Trucco;Alessandro Verri

  • A compact algorithm for rectification of stereo pairs

    Andrea Fusiello;Emanuele Trucco;Alessandro Verri

  • Using machine learning approaches for multi-omics data analysis: A review

    Parminder S. Reel;Smarti Reel;Ewan Pearson;Emanuele Trucco

  • Efficient stereo with multiple windowing

    A. Fusiello;V. Roberto;E. Trucco

  • FABC: Retinal Vessel Segmentation Using AdaBoost

    C A Lupascu;D Tegolo;E Trucco

  • Machine learning of neuroimaging for assisted diagnosis of cognitive impairment and dementia: A systematic review

    Enrico Pellegrini;Lucia Ballerini;Maria del C. Valdes Hernandez;Francesca M. Chappell

  • Making good features track better

    T. Tommasini;A. Fusiello;E. Trucco;V. Roberto

  • Video Tracking: A Concise Survey

    E. Trucco;K. Plakas

  • Self-Tuning Underwater Image Restoration

    E. Trucco;A.T. Olmos-Antillon

  • Validating retinal fundus image analysis algorithms: issues and a proposal.

    Emanuele Trucco;Alfredo Ruggeri;Thomas Karnowski;Luca Giancardo

  • Dictionary of Computer Vision and Image Processing

    Robert B. Fisher;Toby P. Breckon;Kenneth Dawson-Howe;Andrew Fitzgibbon

  • Retinal vessel segmentation using multiwavelet kernels and multiscale hierarchical decomposition

    Yangfan Wang;Guangrong Ji;Ping Lin;Emanuele Trucco

  • Robust motion and correspondence of noisy 3-D point sets with missing data

    Emanuele Trucco;Andrea Fusiello;Vito Roberto

  • Experiments in curvature-based segmentation of range data

    E. Trucco;R.B. Fisher

  • Leveraging Multiscale Hessian-Based Enhancement With a Novel Exudate Inpainting Technique for Retinal Vessel Segmentation

    Roberto Annunziata;Andrea Garzelli;Lucia Ballerini;Alessandro Mecocci

  • Towards automated progress assessment of workpackage components in construction projects using computer vision

    Y. M. Ibrahim;T. C. Lukins;X. Zhang;E. Trucco

  • Improving Feature Tracking with Robust Statistics

    Andrea Fusiello;Emanuele Trucco;Tiziano Tommasini;Vito Roberto

  • Three-dimensional image processing in the future of immersive media

    F. Isgro;E. Trucco;P. Kauff;O. Schreer

  • VAMPIRE: Vessel assessment and measurement platform for images of the REtina

    A Perez-Rovira;T MacGillivray;E Trucco;K S Chin

  • A review of machine learning methods for retinal blood vessel segmentation and artery/vein classification.

    Muthu Rama Krishnan Mookiah;Stephen Hogg;Tom J MacGillivray;Vijayaraghavan Prathiba

  • Model-based planning of optimal sensor placements for inspection

    E. Trucco;M. Umasuthan;A.M. Wallace;V. Roberto

  • Computer and Robot Vision

    Emanuele Trucco

  • Geometric Invariance in Computer Vision

    Emanuele Trucco

Frequent Co-Authors

David M. Lane
David M. Lane Heriot-Watt University
Joanna M. Wardlaw
Joanna M. Wardlaw University of Edinburgh
Yvan Petillot
Yvan Petillot Heriot-Watt University
Andrea Fusiello
Andrea Fusiello University of Udine
Ian J. Deary
Ian J. Deary University of Edinburgh
Stephen J. McKenna
Stephen J. McKenna University of Dundee
Robert B. Fisher
Robert B. Fisher University of Edinburgh
Alessandro Verri
Alessandro Verri University of Genoa
John M. Starr
John M. Starr University of Edinburgh

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