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Francesco Ciompi

Francesco Ciompi

D-Index & Metrics

Computer Science

D-Index
35
Citations
21532
World Ranking
11416
National Ranking
212

Overview

Francesco Ciompi is affiliated with Radboud University in the Netherlands. Their research primarily spans the fields of Medicine and Computer Science, with a strong focus on applications of Artificial Intelligence and machine learning techniques in medical contexts.

Their subfields of study include:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Oncology
  • Cancer Research
  • Molecular Biology

The main topics featured in Francesco Ciompi's work are:

  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Cancer Immunotherapy and Biomarkers
  • Colorectal Cancer Screening and Detection
  • Cancer Genomics and Diagnostics
  • Digital Imaging for Blood Diseases
  • Immunotherapy and Immune Responses

Francesco Ciompi has published in several academic venues, frequently contributing to:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • npj Breast Cancer
  • Modern Pathology
  • bioRxiv (Cold Spring Harbor Laboratory)

Frequent co-authors working alongside Francesco Ciompi include:

  • Jeroen van der Laak
  • Maschenka Balkenhol
  • John-Melle Bokhorst
  • Irıs D. Nagtegaal
  • Witali Aswolinskiy

Notable recent publications include:

  • "Deep learning in histopathology: the path to the clinic" (2021, Nature Medicine)
  • "HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images" (2021, Data Archiving and Networked Services (DANS))
  • "Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer" (2020, npj Breast Cancer)
  • "Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group" (2020, npj Breast Cancer)
  • "Mitosis domain generalization in histopathology images - The MIDOG challenge" (2022, Medical Image Analysis)

Best Publications

  • A survey on deep learning in medical image analysis

    Geert J. S. Litjens;Thijs Kooi;Babak Ehteshami Bejnordi;Arnaud Arindra Adiyoso Setio

  • Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks

    Arnaud Arindra Adiyoso Setio;Francesco Ciompi;Geert Litjens;Paul Gerke

  • Deep learning in histopathology: the path to the clinic

    Jeroen van der Laak;Jeroen van der Laak;Geert Litjens;Francesco Ciompi

  • Quantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology.

    David Tellez;Geert Litjens;Péter Bándi;Wouter Bulten

  • Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks

    David Tellez;Maschenka Balkenhol;Irene Otte-Holler;Rob van de Loo

  • State-of-the-Art Deep Learning in Cardiovascular Image Analysis

    Geert Litjens;Francesco Ciompi;Jelmer M. Wolterink;Bob D. de Vos

  • Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box

    Francesco Ciompi;Bartjan de Hoop;Sarah J. van Riel;Kaman Chung

  • Off-the-shelf convolutional neural network features for pulmonary nodule detection in computed tomography scans

    Bram van Ginneken;Arnaud A. A. Setio;Colin Jacobs;Francesco Ciompi

  • Towards automatic pulmonary nodule management in lung cancer screening with deep learning

    Francesco Ciompi;Kaman Chung;Sarah J. van Riel;Arnaud Arindra Adiyoso Setio

  • Predicting breast tumor proliferation from whole-slide images: The TUPAC16 challenge.

    Mitko Veta;Yujing J. Heng;Nikolas Stathonikos;Babak Ehteshami Bejnordi

  • Neural Image Compression for Gigapixel Histopathology Image Analysis

    David Tellez;Geert Litjens;Jeroen van der Laak;Francesco Ciompi

  • HookNet: Multi-resolution convolutional neural networks for semantic segmentation in histopathology whole-slide images.

    Mart van Rijthoven;Maschenka Balkenhol;Karina Siliņa;Jeroen van der Laak

  • The importance of stain normalization in colorectal tissue classification with convolutional networks

    Francesco Ciompi;Oscar Geessink;Babak Ehteshami Bejnordi;Gabriel Silva de Souza

  • Standardized evaluation methodology and reference database for evaluating IVUS image segmentation

    Simone Balocco;Carlo Gatta;Francesco Ciompi;Andreas Wahle

  • Learning to detect lymphocytes in immunohistochemistry with deep learning

    Zaneta Swiderska-Chadaj;Hans Pinckaers;Mart van Rijthoven;Maschenka Balkenhol

  • Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

    Mohamed Amgad;Elisabeth Specht Stovgaard;Eva Balslev;Jeppe Thagaard

  • Improving airway segmentation in computed tomography using leak detection with convolutional networks.

    Jean-Paul Charbonnier;Eva M. van Rikxoort;Arnaud A.A. Setio;Cornelia M. Schaefer-Prokop

  • Computer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancer

    Oscar G F Geessink;Alexi Baidoshvili;Joost M Klaase;Babak Ehteshami Bejnordi

  • Deep learning assisted mitotic counting for breast cancer.

    Maschenka C A Balkenhol;David Tellez;Willem Vreuls;Pieter C Clahsen

  • Rayleigh Mixture Model for Plaque Characterization in Intravascular Ultrasound

    J C Seabra;F Ciompi;O Pujol;J Mauri

  • HoliMAb: A holistic approach for Media–Adventitia border detection in intravascular ultrasound

    Francesco Ciompi;Oriol Pujol;Carlo Gatta;Marina Alberti

  • Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?

    Kaman Chung;Colin Jacobs;Ernst T. Scholten;Jin Mo Goo

Frequent Co-Authors

Petia Radeva
Petia Radeva University of Barcelona
Bram van Ginneken
Bram van Ginneken Radboud University
Geert Litjens
Geert Litjens Radboud University
Oriol Pujol
Oriol Pujol University of Barcelona
Nasir M. Rajpoot
Nasir M. Rajpoot University of Warwick
Sherene Loi
Sherene Loi Peter MacCallum Cancer Centre
Anant Madabhushi
Anant Madabhushi Emory University
Andreas Maier
Andreas Maier University of Erlangen-Nuremberg
Nico Karssemeijer
Nico Karssemeijer Radboud University
Sibylle Loibl
Sibylle Loibl Goethe University Frankfurt

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