mlsanityData to 7 Oct 2026

ImplicitVol: Sensorless 3D Ultrasound Reconstruction with Deep Implicit Representation

arXiv 2109.12108 ↗First posted 24 Sep 2021eess.IV cs.CVcited by 16

Not on the map. Why?

Abstract (arXiv)

The objective of this work is to achieve sensorless reconstruction of a 3D volume from a set of 2D freehand ultrasound images with deep implicit representation. In contrast to the conventional way that represents a 3D volume as a discrete voxel grid, we do so by parameterizing it as the zero level-set of a continuous function, i.e. implicitly representing the 3D volume as a mapping from the spatial coordinates to the corresponding intensity values. Our proposed model, termed as ImplicitVol, takes a set of 2D scans and their estimated locations in 3D as input, jointly refining the estimated 3D locations and learning a full reconstruction of the 3D volume. When testing on real 2D ultrasound images, novel cross-sectional views that are sampled from ImplicitVol show significantly better visual quality than those sampled from existing reconstruction approaches, outperforming them by over 30% (NCC and SSIM), between the output and ground-truth on the 3D volume testing data. The code will be made publicly available.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 4 of its 24 references that are in the map. First posted on arXiv 24 Sep 2021.

Builds on

4 of 24 references.

References · 4

  1. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,214
  2. 2018On the Spectral Bias of Neural Networkscited by 1,321
  3. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  4. 2019Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networkscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 5; 2025: 5; 2026: 1.

16 papers.

Sort:

  1. 2021Neural Fields in Visual Computing and Beyondcited by 539
  2. 2022DINER: Disorder-Invariant Implicit Neural Representationcited by 30
  3. 2023Ultra-NeRF: Neural Radiance Fields for Ultrasound Imagingcited by 27
  4. 2023Disorder-invariant Implicit Neural Representationcited by 26
  5. 2025UltraGauss: Ultrafast Gaussian Reconstruction of 3D Ultrasound Volumescited by 8
  6. 2024RapidVol: Rapid Reconstruction of 3D Ultrasound Volumes from Sensorless 2D Scanscited by 7
  7. 2024NeRF-US: Removing Ultrasound Imaging Artifacts from Neural Radiance Fields in the Wildcited by 7
  8. 2022Adaptive 3D Localization of 2D Freehand Ultrasound Brain Imagescited by 6
  9. 2024UlRe-NeRF: 3D Ultrasound Imaging through Neural Rendering with Ultrasound Reflection Direction Parameterizationcited by 3
  10. 2025MoNetV2: Enhanced Motion Network for Freehand 3D Ultrasound Reconstructioncited by 3
  11. 20253D Heart Reconstruction from Sparse Pose-agnostic 2D Echocardiographic Slicescited by 1
  12. 2024LiverUSRecon: Automatic 3D Reconstruction and Volumetry of the Liver with a Few Partial Ultrasound Scanscited by 0
4 more
  1. 2024Compact Implicit Neural Representations for Plane Wave Imagescited by 0
  2. 2025X2BR: High-Fidelity 3D Bone Reconstruction from a Planar X-Ray Image with Hybrid Neural Implicit Methodscited by 0
  3. 2025From Slices to Structures: Unsupervised 3D Reconstruction of Female Pelvic Anatomy from Freehand Transvaginal Ultrasoundcited by 0
  4. 2026UltraG-Ray: Physics-Based Gaussian Ray Casting for Novel Ultrasound View Synthesiscited by 0