What question did this study set out to answer?

The aim is to enhance the segmentation of 3D liver anatomy using advanced geometric and attention-based techniques.

April 8, 2026Open Access

GeoTranMesh: a geometry-guided multi-branch mesh transformer for 3d liver segmentation

Key Points

The aim is to enhance the segmentation of 3D liver anatomy using advanced geometric and attention-based techniques.
Utilized a geometry-guided approach for segmentation
Implemented hybrid attention mechanisms
Employed directional multi-branch fusion techniques
Achieved precise segmentation of complex liver structures
Enhanced morphological feature learning
Showed potential for clinical application in liver surgery and augmented reality environments

Abstract

GeoTranMesh integrates hybrid attention and directional multi-branch fusion to enhance geometric consistency and morphological feature learning, achieving precise segmentation of complex anatomical landmarks, demonstrating potential for clinical and AR-guided liver surgery applications.

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Cite This Study

Feng et al. (Mon,) studied this question.

synapsesocial.com/papers/69d5f0bb74eaea4b11a7a1f6 https://doi.org/https://doi.org/10.1007/s11548-026-03600-8

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