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Scaling Ultrasound Volumetric Reconstruction via Mobile Augmented Reality

arXiv 2602.18500 ↗First posted 17 Feb 2026cs.CV cs.ET cs.HCcited by 0

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Abstract (arXiv)

Accurate volumetric characterization of lesions is essential for oncologic diagnosis, risk stratification, and treatment planning. While imaging modalities such as Computed Tomography provide high-quality 3D data, 2D ultrasound (2D-US) remains the preferred first-line modality for breast and thyroid imaging due to cost, portability, and safety factors. However, volume estimates derived from 2D-US suffer from high inter-user variability even among experienced clinicians. Existing 3D ultrasound (3D-US) solutions use specialized probes or external tracking hardware, but such configurations increase costs and diminish portability, constraining widespread clinical use. To address these limitations, we present Mobile Augmented Reality Volumetric Ultrasound (MARVUS), a resource-efficient system designed to increase accessibility to accurate and reproducible volumetric assessment. MARVUS is interoperable with conventional ultrasound (US) systems, using a foundation model to enhance cross-specialty generalization while minimizing hardware requirements relative to current 3D-US solutions. In a user study involving experienced clinicians performing measurements on breast phantoms, MARVUS yielded a substantial improvement in volume estimation accuracy (mean difference: 0.469 cm3) with reduced inter-user variability (mean difference: 0.417 cm3). Additionally, we prove that augmented reality (AR) visualizations enhance objective performance metrics and clinician-reported usability. Collectively, our findings suggests that MARVUS can enhance US-based cancer screening, diagnostic workflows, and treatment planning in a scalable, cost-conscious, and resource-efficient manner. Usage video demonstration available (https://youtu.be/m4llYcZpqmM).

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 3 of its 39 references that are in the map. First posted on arXiv 17 Feb 2026.

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3 of 39 references.

References · 3

  1. 2024A large-scale multicenter breast cancer DCE-MRI benchmark dataset with expert segmentationscited by 40
  2. 2025EdgeTAM: On-Device Track Anything Modelcited by 21
  3. 2023HoloPOCUS: Portable Mixed-Reality 3D Ultrasound Tracking, Reconstruction and Overlaycited by 2

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