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Communication Dans Un Congrès Année : 2024

Unrolled projected gradient algorithm for stain separation in digital histopathological images

Résumé

This paper introduces a novel optimization approach for stain separation in digital histopathological images. Our stain separation cost function incorporates a smooth total variation regularization and is minimized by using a projected gradient algorithm. To enhance computational efficiency and enable supervised learning of the hyperparameters, we further unroll our algorithm into a neural network. The unrolled architecture is not only more efficient for solving the stain separation problem, but also allows to design a highly interpretable and flexible method. Experimental results demonstrate the effectiveness of the proposed unrolled projected gradient algorithm in achieving accurate and visually consistent stain separation.
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Dates et versions

hal-04444439 , version 1 (07-02-2024)

Licence

Copyright (Tous droits réservés)

Identifiants

  • HAL Id : hal-04444439 , version 1

Citer

Aymen Sadraoui, Astrid Laurent-Bellue, Mounir Kaaniche, Amel Benazza-Benyahia, Catherine Guettier, et al.. Unrolled projected gradient algorithm for stain separation in digital histopathological images. IEEE International Conference on Image Processing (ICIP 2024), Oct 2024, Abu Dhabi, United Arab Emirates. ⟨hal-04444439⟩
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