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Aurélio Campilho

Aurélio Campilho

D-Index & Metrics

Computer Science

D-Index
38
Citations
8915
World Ranking
10027
National Ranking
28

Overview

Aurélio Campilho is affiliated with the University of Porto in Portugal. Their research spans primarily across the fields of Medicine and Computer Science, with a strong focus on medical image analysis and artificial intelligence applications within healthcare.

Their main research subfields include Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Ophthalmology, Pulmonary and Respiratory Medicine, and Computer Vision and Pattern Recognition. The topics addressed in their work cover a range of medical imaging and diagnostic applications such as:

  • Radiomics and Machine Learning in Medical Imaging
  • COVID-19 diagnosis using AI
  • AI in cancer detection
  • Retinal Imaging and Analysis
  • Glaucoma and retinal disorders
  • Lung Cancer Diagnosis and Treatment
  • Retinal Diseases and Treatments

Aurélio Campilho has frequently published in venues including:

  • Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
  • Medical Image Analysis
  • Computers in Biology and Medicine
  • Artificial Intelligence in Medicine
  • Scientific Reports

Some of the recent papers authored by Campilho or in collaboration include:

  • DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images, 2020, Medical Image Analysis
  • Data Augmentation for Improving Proliferative Diabetic Retinopathy Detection in Eye Fundus Images, 2020, IEEE Access
  • Microaneurysm detection in color eye fundus images for diabetic retinopathy screening, 2020, Computers in Biology and Medicine
  • O-MedAL: Online active deep learning for medical image analysis, 2020, Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery
  • A multi-task CNN approach for lung nodule malignancy classification and characterization, 2021, Expert Systems with Applications

Their research collaborations include frequent co-authors such as Ana Maria Mendonça, João Pedrosa, Guilherme Aresta, Carlos Ferreira, and Asim Smailagic.

Aurélio Campilho has also contributed to book publications. One notable example is an edited volume titled "Image Analysis and Recognition," published by Springer Science+Business Media in 2020.

Best Publications

  • Segmentation of retinal blood vessels by combining the detection of centerlines and morphological reconstruction

    A.M. Mendonca;A. Campilho

  • Classification of breast cancer histology images using Convolutional Neural Networks

    Teresa Araújo;Guilherme Aresta;Eduardo Castro;José Rouco

  • Image Analysis and Recognition

    Aurélio Campilho;Mohamed S. Kamel

  • BACH: Grand challenge on breast cancer histology images.

    Guilherme Aresta;Teresa Araújo;Scotty Kwok;Sai Saketh Chennamsetty

  • End-to-End Adversarial Retinal Image Synthesis

    Pedro Costa;Adrian Galdran;Maria Ines Meyer;Meindert Niemeijer

  • IDRiD: Diabetic Retinopathy – Segmentation and Grading Challenge

    Prasanna Porwal;Prasanna Porwal;Samiksha Pachade;Manesh Kokare;Girish Deshmukh

  • An Automatic Graph-Based Approach for Artery/Vein Classification in Retinal Images

    Behdad Dashtbozorg;Ana Maria Mendonca;Aurelio Campilho

  • On combining classifiers using sum and product rules

    Luís A. Alexandre;Aurélio C. Campilho;Mohamad Kamel

  • Cell Nuclei and Cytoplasm Joint Segmentation Using the Sliding Band Filter

    Pedro Quelhas;Monica Marcuzzo;Ana Maria Mendonca;Aurélio Campilho

  • Towards Adversarial Retinal Image Synthesis.

    Pedro Costa;Adrian Galdran;Maria Inês Meyer;Michael David Abràmoff

  • DR|GRADUATE: Uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images

    Teresa Araújo;Guilherme Aresta;Luís Mendonça;Susana Penas

  • Optic disc segmentation using the sliding band filter.

    Behdad Dashtbozorg;Ana Maria Mendonça;Aurélio J. C. Campilho

  • CATARACTS: Challenge on automatic tool annotation for cataRACT surgery

    Hassan Al Hajj;Mathieu Lamard;Pierre-Henri Conze;Soumali Roychowdhury

  • Segmentation of the carotid intima-media region in B-mode ultrasound images

    Rui Rocha;Aurélio Campilho;Jorge Silva;Elsa Azevedo

  • Classification of Breast Cancer Histology Images Through Transfer Learning Using a Pre-trained Inception Resnet V2

    Carlos Alexandre Ferreira;Tânia Fernandes Melo;P Sousa;Maria Inês Meyer

  • Performance evaluation of image segmentation

    Fernando C. Monteiro;Aurélio C. Campilho

  • Automatic localization of the optic disc by combining vascular and intensity information.

    Ana Maria Mendonça;António V. Sousa;António V. Sousa;Luís Mendonça;Aurélio J. C. Campilho

  • Hessian based approaches for 3D lung nodule segmentation

    L. Gonçalves;J. Novo;A. Campilho

  • A Weakly-Supervised Framework for Interpretable Diabetic Retinopathy Detection on Retinal Images

    Pedro Costa;Adrian Galdran;Asim Smailagic;Aurelio Campilho

  • iW-Net: an automatic and minimalistic interactive lung nodule segmentation deep network

    Guilherme Aresta;Colin Jacobs;Teresa Araújo;António Cunha

  • Real-time implementation of an optical flow algorithm

    M.V. Correia;A.C. Campilho

Frequent Co-Authors

Mohamed S. Kamel
Mohamed S. Kamel University of Waterloo
Asim Smailagic
Asim Smailagic Carnegie Mellon University
Bram van Ginneken
Bram van Ginneken Radboud University
José Ramos
José Ramos University of Córdoba
Meindert Niemeijer
Meindert Niemeijer Digital Diagnostics Inc.
Michael D. Abràmoff
Michael D. Abràmoff University of Iowa
Max A. Viergever
Max A. Viergever Utrecht University
James A. H. Murray
James A. H. Murray Cardiff University
Ben Scheres
Ben Scheres Wageningen University & Research

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