Towards reliable WMH segmentation under domain shift: An application study using maximum entropy regularization to improve uncertainty estimation.

Journal: Computers in biology and medicine
Published Date: Jul 2, 2025

Abstract

BACKGROUND: Accurate segmentation of white matter hyperintensities (WMH) is crucial for clinical decision-making, particularly in the context of multiple sclerosis. However, domain shifts, such as variations in MRI machine types or acquisition parameters, pose significant challenges to model calibration and uncertainty estimation. This comparative study investigates the impact of domain shift on WMH segmentation, proposing maximum-entropy regularization techniques to enhance model calibration and uncertainty estimation. The purpose is to identify errors appearing after model deployment in clinical scenarios using predictive uncertainty as a proxy measure, since it does not require ground-truth labels to be computed.

Authors

  • Franco Matzkin
    Institute for Signals, Systems and Computational Intelligence, sinc(i) CONICET-UNL, Santa Fe, Argentina. Electronic address: fmatzkin@sinc.unl.edu.ar.
  • Agostina Larrazabal
    Tryolabs, Uruguay.
  • Diego H Milone
  • Jose Dolz
    AQUILAB, Biocentre A. Fleming, 250 rue Salvador Allende, 59120, Loos les Lille, France. jose.dolz.upv@gmail.com.
  • Enzo Ferrante

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