# UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumes

arXiv: https://arxiv.org/abs/2505.05643 · HTML: https://mlsanity.com/paper/2505.05643/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 36 references that are in the map.
- First posted on arXiv 8 May 2025.

## Builds on (most cited first, 13 of 13)

- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [3D Gaussian Splatting for Real-Time Radiance Field Rendering](https://mlsanity.com/paper/2308.04079/) (2023)
- [Plenoxels: Radiance Fields without Neural Networks](https://mlsanity.com/paper/2112.05131/) (2021)
- [2D Gaussian Splatting for Geometrically Accurate Radiance Fields](https://mlsanity.com/paper/2403.17888/) (2024)
- [Mip-Splatting: Alias-free 3D Gaussian Splatting](https://mlsanity.com/paper/2311.16493/) (2023)
- [gsplat: An Open-Source Library for Gaussian Splatting](https://mlsanity.com/paper/2409.06765/) (2024)
- [Revising Densification in Gaussian Splatting](https://mlsanity.com/paper/2404.06109/) (2024)
- [R2-Gaussian: Rectifying Radiative Gaussian Splatting for Tomographic Reconstruction](https://mlsanity.com/paper/2405.20693/) (2024)
- [Gaussian Splatting: 3D Reconstruction and Novel View Synthesis, a Review](https://mlsanity.com/paper/2405.03417/) (2024)
- [Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstruction](https://mlsanity.com/paper/2407.02918/) (2024)
- [ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation](https://mlsanity.com/paper/2109.12108/) (2021)
- [Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction from Freehand 2D Ultrasound Videos](https://mlsanity.com/paper/2405.13235/) (2024)
- [Ultrasound Plane Pose Regression: Assessing Generalized Pose Coordinates in the Fetal Brain](https://mlsanity.com/paper/2301.08317/) (2023)

## Built on by (most cited first, 8 of 8)

- [TUS-REC2024: A Challenge to Reconstruct 3D Freehand Ultrasound Without External Tracker](https://mlsanity.com/paper/2506.21765/) (2025)
- [From Slices to Structures: Unsupervised 3D Reconstruction of Female Pelvic Anatomy from Freehand Transvaginal Ultrasound](https://mlsanity.com/paper/2508.14552/) (2025)
- [Medical Scene Reconstruction and Segmentation based on 3D Gaussian Representation](https://mlsanity.com/paper/2512.22800/) (2025)
- [UltraG-Ray: Physics-Based Gaussian Ray Casting for Novel Ultrasound View Synthesis](https://mlsanity.com/paper/2603.29022/) (2026)
- [Rendering Novel Views of MRI Using 3D Gaussian Splatting](https://mlsanity.com/paper/2606.26236/) (2026)
- [K-space Gaussian Representation for Parallel MRI](https://mlsanity.com/paper/2608.00075/) (2026)
- [PAGS: Autofocusing Photoacoustic Tomography via Speed-of-Sound-Adaptive Gaussian Splatting](https://mlsanity.com/paper/2608.25472/) (2026)
- [Shadow Reduction in Ultrasound Imaging Using Differentiable Simulation and Radiance Field Decomposition](https://mlsanity.com/paper/2609.29373/) (2026)

## Abstract (arXiv)

Ultrasound imaging is widely used due to its safety, affordability, and real-time capabilities, but its 2D interpretation is highly operator-dependent, leading to variability and increased cognitive demand. 2D-to-3D reconstruction mitigates these challenges by providing standardized volumetric views, yet existing methods are often computationally expensive, memory-intensive, or incompatible with ultrasound physics. We introduce UltraGauss: the first ultrasound-specific Gaussian Splatting framework, extending view synthesis techniques to ultrasound wave propagation. Unlike conventional perspective-based splatting, UltraGauss models probe-plane intersections in 3D, aligning with acoustic image formation. We derive an efficient rasterization boundary formulation for GPU parallelization and introduce a numerically stable covariance parametrization, improving computational efficiency and reconstruction accuracy. On real clinical ultrasound data, UltraGauss achieves state-of-the-art reconstructions in 5 minutes, and reaching 0.99 SSIM within 20 minutes on a single GPU. A survey of expert clinicians confirms UltraGauss' reconstructions are the most realistic among competing methods. Our CUDA implementation will be released upon publication.