World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
35
Citations
5068
World Ranking
8978
National Ranking
211

Overview

Xavier Descombes is affiliated with the French Institute for Research in Computer Science and Automation (INRIA) in France. Their research spans fields such as Medicine and Computer Science, with a particular focus on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology, Biophysics, and Molecular Biology.

Their work involves several main research topics including AI in cancer detection, Radiomics and Machine Learning in Medical Imaging, Cell Image Analysis Techniques, Colorectal Cancer Screening and Detection, Skin Protection and Aging, Neonatal skin health care, and Medical Image Segmentation Techniques.

Descombes has published in various venues, notably:

  • Journal of Biomedical Optics
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Journal of Cell Science
  • Scientific Reports
  • International Journal of Biomedical Engineering and Technology

Some of their recent papers include:

  • Fibronectin Extra Domains tune cellular responses and confer topographically distinct features to fibril networks, 2021, Journal of Cell Science
  • Automating reflectance confocal microscopy image analysis for dermatological research: a review, 2022, Journal of Biomedical Optics
  • Multi-feature-based approach for white blood cells segmentation and classification in peripheral blood and bone marrow images, 2021, International Journal of Biomedical Engineering and Technology
  • Improving CNNs classification with pathologist-based expertise: the renal cell carcinoma case study, 2023, Scientific Reports
  • Biological Image Segmentation Using Region-Scalable Fitting Energy with B-Spline Level Set Implementation and Watershed, 2022, IRBM

Descombes frequently collaborates with a group of co-authors, including:

  • Damien Ambrosetti
  • Éric Debreuve
  • Francesco Ponzio
  • Imane Lboukili
  • Georgios N. Stamatas

Their research contributions show consistent interlinking of computer science techniques with medical and biological applications, particularly through the use of AI and machine learning methodologies in cancer detection and medical image processing. This multidisciplinary approach highlights their involvement in advancing imaging analysis and segmentation techniques, which are crucial for clinical diagnostics and biomedical research.

Best Publications

  • A Gibbs Point Process for Road Extraction from Remotely Sensed Images

    Radu Stoica;Xavier Descombes;Josiane Zerubia

  • Point processes for unsupervised line network extraction in remote sensing

    C. Lacoste;X. Descombes;J. Zerubia

  • Structural Approach for Building Reconstruction from a Single DSM

    F. Lafarge;X. Descombes;J. Zerubia;M. Pierrot-Deseilligny

  • Building Development Monitoring in Multitemporal Remotely Sensed Image Pairs with Stochastic Birth-Death Dynamics

    C. Benedek;X. Descombes;J. Zerubia

  • Estimation of Markov random field prior parameters using Markov chain Monte Carlo maximum likelihood

    X. Descombes;R.D. Morris;J. Zerubia;M. Berthod

  • Texture feature analysis using a gauss-Markov model in hyperspectral image classification

    G. Rellier;X. Descombes;F. Falzon;J. Zerubia

  • Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions

    Morten Larsen;Mats Eriksson;Xavier Descombes;Guillaume Perrin

  • Automatic Building Extraction from DEMs using an Object Approach and Application to the 3D-city Modeling

    Florent Lafarge;Xavier Descombes;Josiane Zerubia;Marc Pierrot-Deseilligny

  • Building Outline Extraction from Digital Elevation Models Using Marked Point Processes

    Mathias Ortner;Xavier Descombes;Josiane Zerubia

  • Spatio-temporal fMRI analysis using Markov random fields

    X. Descombes;F. Kruggel;D.Y. Von Cramon

  • Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum

    Xavier Descombes;Robert Minlos;Elena Zhizhina

  • Geometric Feature Extraction by a Multimarked Point Process

    F Lafarge;Georgy Gimel'farb;X Descombes

  • Coastline detection by a Markovian segmentation on SAR images

    Xavier Descombes;Miguel Moctezuma;Henri Maître;Jean-Paul Rudant

  • A Marked Point Process of Rectangles and Segments for Automatic Analysis of Digital Elevation Models

    M. Ortner;X. Descombes;J. Zerubia

  • Marked point process in image analysis

    X. Descombes;J. Zerubia

  • fMRI Signal Restoration Using a Spatio-Temporal Markov Random Field Preserving Transitions

    Xavier Descombes;Frithjof Kruggel;D.Yves von Cramon

  • Estimating Gaussian Markov random field parameters in a nonstationary framework: application to remote sensing imaging

    X. Descombes;M. Sigelle;F. Preteux

  • A marked point process model for tree crown extraction in plantations

    G. Perrin;X. Descombes;J. Zerubia

  • Texture Analysis through a Markovian Modelling and FuzzyClassification: Application to Urban Area Extraction fromSatellite Images

    A. Lorette;X. Descombes;J. Zerubia

  • Comparison of filtering methods for fMRI datasets.

    F. Kruggel;D.Y. von Cramon;X. Descombes

Frequent Co-Authors

Josiane Zerubia
Josiane Zerubia French Institute for Research in Computer Science and Automation - INRIA
Marc Pierrot-Deseilligny
Marc Pierrot-Deseilligny Gustave Eiffel University
Grégoire Malandain
Grégoire Malandain French Institute for Research in Computer Science and Automation - INRIA
D. Yves von Cramon
D. Yves von Cramon Max Planck Institute for Human Cognitive and Brain Sciences
Pierre Couteron
Pierre Couteron Institut de Recherche pour le Développement
Georgy Gimel'farb
Georgy Gimel'farb University of Auckland
Michèle Studer
Michèle Studer Université Côte d'Azur
Pierre Degond
Pierre Degond Toulouse Mathematics Institute
José Luiz Stape
José Luiz Stape North Carolina State University

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