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Computer Science

D-Index
44
Citations
32158
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7342
National Ranking
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Overview

Geert Litjens is affiliated with Radboud University in the Netherlands and has a research focus that spans medicine and computer science, particularly in the areas of artificial intelligence, radiology, nuclear medicine, imaging, and oncology. Their work prominently intersects with the application of AI and machine learning in healthcare, especially for cancer detection and diagnosis.

Their publication record includes significant contributions to topics such as:

  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Artificial Intelligence in Healthcare and Education
  • Prostate Cancer Diagnosis and Treatment
  • Advanced Neural Network Applications
  • COVID-19 diagnosis using AI
  • Pancreatic and Hepatic Oncology Research

Recent papers authored or co-authored by Geert Litjens include:

  • "The Medical Segmentation Decathlon" (2022) published in Nature Communications
  • "Deep learning in histopathology: the path to the clinic" (2021) published in Nature Medicine
  • "Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study" (2020) published in The Lancet Oncology
  • "The 2019 International Society of Urological Pathology (ISUP) Consensus Conference on Grading of Prostatic Carcinoma" (2020) published in The American Journal of Surgical Pathology
  • "Metrics reloaded: recommendations for image analysis validation" (2024) published in Nature Methods

Frequent co-authors collaborating with Geert Litjens include Jeroen van der Laak, Bram van Ginneken, Henkjan Huisman, Hans Pinckaers, and Michela Antonelli.

Publications by Geert Litjens often appear in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Medical Image Analysis
  • European Urology
  • IEEE Journal of Biomedical and Health Informatics

Geert Litjens has also authored a book titled "Diagnosing and staging of periampullary adenocarcinoma," published in 2024 by Radboud University Press eBooks.

Best Publications

  • A survey on deep learning in medical image analysis

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

  • Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.

    Babak Ehteshami Bejnordi;Mitko Veta;Paul Johannes van Diest;Bram van Ginneken

  • The 2005 International Society of Urological Pathology (ISUP) consensus conference on Gleason grading of prostatic carcinoma

    Geert J.L.H. van Leenders;Theodorus H. van der Kwast;David J. Grignon;Andrew J. Evans

  • 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 as a tool for increased accuracy and efficiency of histopathological diagnosis

    Geert Litjens;Clara I. Sánchez;Nadya Timofeeva;Meyke Hermsen

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

  • Large scale deep learning for computer aided detection of mammographic lesions

    Thijs Kooi;Geert J. S. Litjens;Bram van Ginneken;Albert Gubern-Mérida

  • A large annotated medical image dataset for the development and evaluation of segmentation algorithms

    Amber L. Simpson;Michela Antonelli;Spyridon Bakas;Michel Bilello

  • Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge.

    Geert J. S. Litjens;Robert Toth;Wendy J. M. van de Ven;Caroline Hoeks

  • 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

  • From Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 Challenge

    Peter Bandi;Oscar Geessink;Quirine Manson;Marcory Van Dijk

  • Computer-Aided Detection of Prostate Cancer in MRI

    Geert Litjens;Oscar Debats;Jelle Barentsz;Nico Karssemeijer

  • 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

  • Stain Specific Standardization of Whole-Slide Histopathological Images

    Babak Ehteshami Bejnordi;Geert Litjens;Nadya Timofeeva;Irene Otte-Holler

  • Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities.

    Mohsen Ghafoorian;Nico Karssemeijer;Tom Heskes;Inge W. M. van Uden

  • Neural Image Compression for Gigapixel Histopathology Image Analysis

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

  • Using deep learning to segment breast and fibroglandular tissue in MRI volumes

    Mehmet Ufuk Dalmış;Geert Litjens;Katharina Holland;Arnaud Setio

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

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

  • Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images

    Babak Ehteshami Bejnordi;Guido C. A. Zuidhof;Maschenka Balkenhol;Meyke Hermsen

  • Automated Gleason Grading of Prostate Biopsies using Deep Learning.

    Wouter Bulten;Hans Pinckaers;Hester van Boven;Robert Vink

Frequent Co-Authors

Bram van Ginneken
Bram van Ginneken Radboud University
Nico Karssemeijer
Nico Karssemeijer Radboud University
Francesco Ciompi
Francesco Ciompi Radboud University
Clara I. Sánchez
Clara I. Sánchez University of Amsterdam
Anant Madabhushi
Anant Madabhushi Emory University
Ronald M. Summers
Ronald M. Summers National Institutes of Health
Bjoern H. Menze
Bjoern H. Menze University of Zurich
Bennett A. Landman
Bennett A. Landman Vanderbilt University
Lena Maier-Hein
Lena Maier-Hein German Cancer Research Center
Qi Dou
Qi Dou Chinese University of Hong Kong

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