Deform any Liver in Real-Time

This paper introduces Deform Any Liver (DAL), a real-time surrogate model designed to accurately predict any liver deformation, given a set of applied forces. DAL leverages a hypernetwork to condition a U-Net architecture on the liver shape, with the U-Net receiving the applied external forces as input to predict the resulting displacement field. This design enables the model to generalize across various patient geometries, overcoming the limitations of existing patient-specific approaches. The DAL model is trained, validated, and tested using real human liver geometries, employing finite element method (FEM) simulations to generate realistic deformation data. Our results demonstrate the model's effectiveness and adaptability in accurately predicting the deformation of various liver shapes.

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Publication Details

Published
2025-04-14
DOI
https://doi.org/10.1109/isbi60581.2025.10981061
Citations
1
Primary Topic
Liver physiology and pathology
Type
article
Field-Weighted Citation Impact
1.32

Funders

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article

Deform any Liver in Real-Time

Sidaty El Hadramy, Stéphane Cotin, Nicolas Padoy
1 citations
Liver physiology and pathology
1.32
article

Deform any Liver in Real-Time

Sidaty El Hadramy, Stéphane Cotin, Nicolas Padoy
article en
1 citations

Abstract

This paper introduces Deform Any Liver (DAL), a real-time surrogate model designed to accurately predict any liver deformation, given a set of applied forces. DAL leverages a hypernetwork to condition a U-Net architecture on the liver shape, with the U-Net receiving the applied external forces as input to predict the resulting displacement field. This design enables the model to generalize across various patient geometries, overcoming the limitations of existing patient-specific approaches. The DAL model is trained, validated, and tested using real human liver geometries, employing finite element method (FEM) simulations to generate realistic deformation data. Our results demonstrate the model's effectiveness and adaptability in accurately predicting the deformation of various liver shapes.

Centre National de la Recherche Scientifique (FR), Inserm (FR), Institut de Recherche contre les Cancers de l’Appareil Digestif (FR), Université de Strasbourg (FR)
Agence Nationale de la Recherche
Zero hunger
Openalex Percentile: Top 25%
Liver physiology and pathology
1.32
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