World's Best Scientists 2026 revealed!
Ender Konukoglu

Ender Konukoglu

D-Index & Metrics

Computer Science

D-Index
54
Citations
18456
World Ranking
4453
National Ranking
97

Overview

Ender Konukoglu is affiliated with ETH Zurich in Switzerland and has extensively contributed to the fields of computer science and medicine. Their research primarily focuses on computer vision, pattern recognition, radiology, nuclear medicine and imaging, artificial intelligence, biomedical engineering, and surgery.

Their main areas of study include radiomics and machine learning in medical imaging, advanced neural network applications, medical image segmentation techniques, domain adaptation and few-shot learning, medical imaging techniques and applications, medical imaging and analysis, and 3D shape modeling and analysis.

Konukoglu has authored several recent papers across notable venues. These include:

  • Exploring Cross-Image Pixel Contrast for Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Rethinking Semantic Segmentation: A Prototype View, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Contrastive learning of global and local features for medical image segmentation with limited annotations, 2020, arXiv (Cornell University)
  • Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation, 2023, Medical Image Analysis
  • Test-time adaptable neural networks for robust medical image segmentation, 2020, Medical Image Analysis

Frequent publication venues include:

  • arXiv (Cornell University)
  • Medical Image Analysis
  • Osteoarthritis and Cartilage
  • Lecture notes in computer science
  • Nature Communications

Frequent co-authors collaborating with Konukoglu are Ertunç Erdil, Luc Van Gool, Gustav Bredell, Neerav Karani, and Christian F. Baumgartner.

Konukoglu has also contributed to book publications, including the volume titled Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning, published in 2021 by Springer Science+Business Media.

Best Publications

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer

  • Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold, Learning and Semi-supervised Learning

    Antonio Criminisi;Jamie Shotton;Ender Konukoglu

  • Exploring Cross-Image Pixel Contrast for Semantic Segmentation

    Wenguan Wang;Tianfei Zhou;Fisher Yu;Jifeng Dai

  • Rethinking Semantic Segmentation: A Prototype View

    Unknown

  • Shape-based hand recognition

    E. Yoruk;E. Konukoglu;B. Sankur;J. Darbon

  • Regression forests for efficient anatomy detection and localization in CT studies

    Antonio Criminisi;Jamie Shotton;Duncan Robertson;Ender Konukoglu

  • Decision Forests for Classification, Regression, Density Estimation, Manifold Learning and Semi-Supervised Learning

    Antonio Criminisi;Ender Konukoglu;Jamie Shotton

  • Decision forests for tissue-specific segmentation of high-grade gliomas in multi-channel MR.

    Darko Zikic;Ben Glocker;Ender Konukoglu;Antonio Criminisi

  • Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images.

    Ezequiel Geremia;Olivier Clatz;Bjoern H. Menze;Ender Konukoglu

  • Regression forests for efficient anatomy detection and localization in computed tomography scans

    Antonio Criminisi;Duncan P. Robertson;Ender Konukoglu;Jamie Shotton

  • An Exploration of 2D and 3D Deep Learning Techniques for Cardiac MR Image Segmentation

    Christian F. Baumgartner;Lisa M. Koch;Marc Pollefeys;Ender Konukoglu

  • Image Guided Personalization of Reaction-Diffusion Type Tumor Growth Models Using Modified Anisotropic Eikonal Equations

    E. Konukoglu;O. Clatz;B.H. Menze;B. Stieltjes

  • Automatic Localization and Identification of Vertebrae in Arbitrary Field-of-View CT Scans

    Ben Glocker;Johannes Feulner;Antonio Criminisi;David R. Haynor

  • Unsupervised Detection of Lesions in Brain MRI using Constrained Adversarial Auto-encoders

    Xiaoran Chen;Ender Konukoglu

  • Local contrastive loss with pseudo-label based self-training for semi-supervised medical image segmentation

    Unknown

  • Vertebrae localization in pathological spine CT via dense classification from sparse annotations.

    Ben Glocker;Darko Zikic;Ender Konukoglu;David R. Haynor

  • Clinical Prediction from Structural Brain MRI Scans: A Large-Scale Empirical Study

    Mert R. Sabuncu;Mert R. Sabuncu;Ender Konukoglu

  • PHiSeg: Capturing Uncertainty in Medical Image Segmentation

    Christian F. Baumgartner;Kerem Can Tezcan;Krishna Chaitanya;Andreas M. Hötker

  • Test-time adaptable neural networks for robust medical image segmentation

    Neerav Karani;Ertunc Erdil;Krishna Chaitanya;Ender Konukoglu

  • Glioma Dynamics and Computational Models: A Review of Segmentation, Registration, and In Silico Growth Algorithms and their Clinical Applications

    Elsa D. Angelini;Olivier Clatz;Emmanuel Mandonnet;Ender Konukoglu

  • Is Synthesizing MRI Contrast Useful for Inter-modality Analysis?

    Juan Eugenio Iglesias;Ender Konukoglu;Darko Zikic;Ben Glocker

  • Extrapolating glioma invasion margin in brain magnetic resonance images: Suggesting new irradiation margins

    Ender Konukoglu;Olivier Clatz;Pierre-Yves Bondiau;Hervé Delingette

Frequent Co-Authors

Ben Glocker
Ben Glocker Imperial College London
Nicholas Ayache
Nicholas Ayache French Institute for Research in Computer Science and Automation - INRIA
Antonio Criminisi
Antonio Criminisi Microsoft (United States)
Bjoern H. Menze
Bjoern H. Menze University of Zurich
Hervé Delingette
Hervé Delingette French Institute for Research in Computer Science and Automation - INRIA
Bruce Fischl
Bruce Fischl Harvard University
Marc Pollefeys
Marc Pollefeys ETH Zurich
Jamie Shotton
Jamie Shotton Microsoft (United States)
Metin Sitti
Metin Sitti Max Planck Institute for Intelligent Systems
Maxime Sermesant
Maxime Sermesant Université Côte d'Azur

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