World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
13279
World Ranking
9959
National Ranking
397

Overview

Tal Arbel is affiliated with McGill University in Canada and specializes in research at the intersection of computer science and medicine. Their work spans over 81 publications in computer science and 68 in medicine, with a focus on subfields such as artificial intelligence, radiology, nuclear medicine and imaging, computer vision and pattern recognition, health informatics, and neurology.

Their research topics primarily cover radiomics and machine learning in medical imaging, AI in cancer detection, artificial intelligence in healthcare and education, explainable artificial intelligence (XAI), brain tumor detection and classification, medical image segmentation techniques, and advanced neural network applications.

Tal Arbel has contributed scholarly work to various publication venues. Frequent venues include:

  • arXiv (Cornell University)
  • Nature Methods
  • The Journal of Machine Learning for Biomedical Imaging
  • Medical Image Analysis
  • IEEE Transactions on Medical Imaging

Co-authorship collaborations have featured repeatedly with the following researchers:

  • Brennan Nichyporuk
  • Douglas L. Arnold
  • Raghav Mehta
  • Jean-Pierre Falet
  • Sotirios A. Tsaftaris

Representative recent papers by Tal Arbel include:

  • "Metrics reloaded: recommendations for image analysis validation" (2024), published in Nature Methods
  • "Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation" (2023), published on arXiv (Cornell University)
  • "Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis" (2020), published in Scientific Reports
  • "Understanding metric-related pitfalls in image analysis validation" (2024), published in Nature Methods
  • "Common Limitations of Image Processing Metrics: A Picture Story" (2021), published on arXiv (Cornell University)

Tal Arbel has also contributed to academic books, including a publication with Springer Science+Business Media titled "Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis" (2020).

Best Publications

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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

  • 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

  • Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

    M. Jorge Cardoso;Tal Arbel;Gustavo Carneiro;Tanveer Syeda-Mahmood

  • Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

    K. Murphy;B. van Ginneken;J. M. Reinhardt;S. Kabus

  • Exploring uncertainty measures in deep networks for Multiple sclerosis lesion detection and segmentation.

    Tanya Nair;Doina Precup;Douglas L. Arnold;Tal Arbel

  • Longitudinal multiple sclerosis lesion segmentation: Resource and challenge.

    Aaron Carass;Snehashis Roy;Amod Jog;Jennifer L. Cuzzocreo

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

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

  • Evaluating intensity normalization on MRIs of human brain with multiple sclerosis.

    Mohak Shah;Yiming Xiao;Nagesh K. Subbanna;Simon J. Francis

  • Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis

    Aaron Carass;Snehashis Roy;Adrian Gherman;Jacob C. Reinhold

  • Detection, Localization, and Sex Classification of Faces from Arbitrary Viewpoints and under Occlusion

    M. Toews;T. Arbel

  • Feature-based morphometry: discovering group-related anatomical patterns.

    Matthew Toews;William M. Wells Iii;William M. Wells Iii;D. Louis Collins;Tal Arbel

  • Viewpoint selection by navigation through entropy maps

    T. Arbel;F.P. Ferrie

  • Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images

    Rashed Karim;Pranav Bhagirath;Piet Claus;R. James Housden

  • BIAS: Transparent reporting of biomedical image analysis challenges.

    Lena Maier-Hein;Annika Reinke;Michal Kozubek;Anne L. Martel

  • IBIS: an OR ready open-source platform for image-guided neurosurgery

    Simon Drouin;Anna Kochanowska;Marta Kersten-Oertel;Ian J. Gerard

  • Entropy-based gaze planning

    Tal Arbel;Frank P Ferrie

  • Multi-Modal Image Registration Based on Gradient Orientations of Minimal Uncertainty

    Dante De Nigris;D. L. Collins;T. Arbel

  • Temporally Consistent Probabilistic Detection of New Multiple Sclerosis Lesions in Brain MRI

    Colm Elliott;Douglas L. Arnold;D. Louis Collins;Tal Arbel

  • Common Limitations of Image Processing Metrics: A Picture Story

    Annika Reinke;Matthias Eisenmann;Minu Dietlinde Tizabi;Carole H. Sudre

  • Automatic non-linear MRI-ultrasound registration for the correction of intra-operative brain deformations.

    Tal Arbel;Xavier Morandi;Roch Comeau;D. Collins

  • Hierarchical probabilistic Gabor and MRF segmentation of brain tumours in MRI volumes.

    Nagesh K. Subbanna;Doina Precup;D. Louis Collins;Tal Arbel

  • Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI Using Conditional Random Fields

    Z. Karimaghaloo;M. Shah;S. J. Francis;D. L. Arnold

  • Automatic Non-linear MRI-Ultrasound Registration for the Correction of Intra-operative Brain Deformations

    Tal Arbel;Xavier Morandi;Roch M. Comeau;D. Louis Collins

  • Intravascular Imaging and Computer Assisted Stenting, and Large-Scale Annotation of Biomedical Data and Expert Label Synthesis

    M.J. Cardoso;T. Arbel;V. Cheplygina;S.-L. Lee

  • BIAS: Transparent reporting of biomedical image analysis challenges

    Lena Maier-Hein;Annika Reinke;Michal Kozubek;Anne L. Martel

Frequent Co-Authors

Douglas L. Arnold
Douglas L. Arnold Montreal Neurological Institute and Hospital
Doina Precup
Doina Precup McGill University
Bjoern H. Menze
Bjoern H. Menze University of Zurich
Henning Müller
Henning Müller University of Applied Sciences and Arts Western Switzerland
Pierre Jannin
Pierre Jannin University of Rennes
Bennett A. Landman
Bennett A. Landman Vanderbilt University
Lena Maier-Hein
Lena Maier-Hein German Cancer Research Center
Bram van Ginneken
Bram van Ginneken Radboud University
Klaus H. Maier-Hein
Klaus H. Maier-Hein German Cancer Research Center

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