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Computer Science
Switzerland
2025

D-Index & Metrics

Computer Science

D-Index
65
Citations
31268
World Ranking
2389
National Ranking
56

Research.com Recognitions

  • 2025 - Research.com Computer Science in Switzerland Leader Award
  • 2022 - Research.com Computer Science in Switzerland Leader Award

Overview

Bjoern H. Menze is affiliated with the University of Zurich in Switzerland. Their research focuses primarily on the intersection of medicine and computer science, with notable contributions across several specialized subfields.

The main fields of study encompassed in Menze's work include:

  • Medicine
  • Computer Science

Within these broad areas, their subfields of study are:

  • Radiology, Nuclear Medicine and Imaging
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Artificial Intelligence
  • Neurology

Menze's research topics cover a range of applications and developments in medical imaging and analysis, including:

  • Radiomics and Machine Learning in Medical Imaging
  • Medical Imaging and Analysis
  • Medical Imaging Techniques and Applications
  • Advanced MRI Techniques and Applications
  • AI in cancer detection
  • Medical Image Segmentation Techniques
  • Advanced Neural Network Applications

They have authored several recent papers, including:

  • The Medical Segmentation Decathlon, 2022, Nature Communications
  • associated_data_Investigating the Effectiveness of clDice Loss for Road Crack Segmentation, 2025, arXiv (Cornell University)
  • Machine learning analysis of whole mouse brain vasculature, 2020, Nature Methods
  • VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images, 2021, Medical Image Analysis
  • Metrics reloaded: recommendations for image analysis validation, 2024, Nature Methods

Frequent coauthors with whom Menze has collaborated extensively include:

  • Benedikt Wiestler
  • Ivan Ezhov
  • Jan S. Kirschke
  • Hongwei Li
  • Suprosanna Shit

The primary venues for their publications are:

  • arXiv (Cornell University)
  • Zurich Open Repository and Archive (University of Zurich)
  • Medical Image Analysis
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition

Best Publications

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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

  • The Multimodal Brain TumorImage Segmentation Benchmark (BRATS)

    Bjoern Menze;Mauricio Reyes;Koen Van Leemput;Nicole Porz

  • Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

    Spyridon Bakas;Mauricio Reyes;Andras Jakab;Stefan Bauer

  • A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

    Bjoern H Menze;B Michael Kelm;Ralf Masuch;Uwe Himmelreich

  • The Liver Tumor Segmentation Benchmark (LiTS)

    Patrick Bilic;Patrick Ferdinand Christ;Eugene Vorontsov;Grzegorz Chlebus

  • The Medical Segmentation Decathlon

    Michela Antonelli;Annika Reinke;Spyridon Bakas;Keyvan Farahani

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

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

  • Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

    Patrick Ferdinand Christ;Mohamed Ezzeldin A. Elshaer;Florian Ettlinger;Sunil Tatavarty

  • ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI

    Oskar Maier;Bjoern H. Menze;Janina von der Gablentz;Levin Häni

  • Multi-Centre, Multi-Vendor and Multi-Disease Cardiac Segmentation: The M&Ms Challenge.

    Víctor M. Campello;Polyxeni Gkontra;Cristian Izquierdo;Carlos Martín-Isla

  • Federated learning enables big data for rare cancer boundary detection

    Unknown

  • clDice - a Novel Topology-Preserving Loss Function for Tubular Structure Segmentation

    Suprosanna Shit;Johannes C. Paetzold;Anjany Sekuboyina;Ivan Ezhov

  • Why rankings of biomedical image analysis competitions should be interpreted with care

    Lena Maier-Hein;Matthias Eisenmann;Annika Reinke;Sinan Onogur

  • Machine learning analysis of whole mouse brain vasculature.

    Mihail Ivilinov Todorov;Johannes Christian Paetzold;Oliver Schoppe;Giles Tetteh

  • VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images

    Anjany Sekuboyina;Malek E. Husseini;Amirhossein Bayat;Maximilian Löffler

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

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

  • A generative model for brain tumor segmentation in multi- modal images

    Bjoern H. Menze;Koen Van Leemput;Danial Lashkari;Marc-André Weber

  • On oblique random forests

    Bjoern H. Menze;B. Michael Kelm;Daniel N. Splitthoff;Ullrich Koethe

  • Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks.

    Patrick Ferdinand Christ;Florian Ettlinger;Felix Grün;Mohamed Ezzeldin A. Elshaera

  • Fully convolutional network ensembles for white matter hyperintensities segmentation in MR images.

    Hongwei Li;Gongfa Jiang;Jianguo Zhang;Ruixuan Wang

  • Robust prediction of the MASCOT score for an improved quality assessment in mass spectrometric proteomics

    Thomas Koenig;Bjoern H. Menze;Marc Kirchner;Flavio Monigatti

  • A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

    Bjoern Holger Menze;Bernd Michael Kelm;Ralf Masuch;Uwe Himmerlreich

Frequent Co-Authors

Georg Langs
Georg Langs Medical University of Vienna
Fred A. Hamprecht
Fred A. Hamprecht Heidelberg University
Henning Müller
Henning Müller University of Applied Sciences and Arts Western Switzerland
Nicholas Ayache
Nicholas Ayache French Institute for Research in Computer Science and Automation - INRIA
Koen Van Leemput
Koen Van Leemput Harvard University
Jianguo Zhang
Jianguo Zhang Southern University of Science and Technology
Mauricio Reyes
Mauricio Reyes University of Bern
Tal Arbel
Tal Arbel McGill University

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