Ultrasound volume reconstruction from 2D Freehand acquisitions using neural implicit representations - Structural Models and Tools in Computer Graphics Access content directly
Conference Papers Year : 2024

Ultrasound volume reconstruction from 2D Freehand acquisitions using neural implicit representations

Abstract

3D ultrasound reconstruction allows physicians to explore a region of interest (ROI) in 3D while leveraging the advantages of 2D ultrasound imaging: simple, low cost and non-ionizing. It may assist many clinical tasks, such as organ measurement, procedure control or visualization of tissues difficult to interpret through 2D visualization. Recently, new deep learning techniques in the field of novel view synthesis, based on a continuous description of the 3D field, showed promising results in terms of 3D model estimation, robustness to noise and uncertainty, and efficiency. Inspired by these approaches, the objective of this work is to propose a 3D ultrasound reconstruction method based on neural implicit representations. Results on simulated and experimental data show the superiority of the proposed method compared to state-of-the-art voxel-based reconstruction.
Fichier principal
Vignette du fichier
_François__Neural_Ultrasound_Field-4.pdf (2.79 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04480668 , version 1 (27-02-2024)

Identifiers

  • HAL Id : hal-04480668 , version 1

Cite

François Gaits, Nicolas Mellado, Adrian Basarab. Ultrasound volume reconstruction from 2D Freehand acquisitions using neural implicit representations. 21st IEEE International Symposium on Biomedical Imaging (ISBI 2024), IEEE Signal Processing Society; IEEE Engineering in Medicine and Biology Society, May 2024, Athènes, Greece. à paraître. ⟨hal-04480668⟩
110 View
65 Download

Share

Gmail Mastodon Facebook X LinkedIn More