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AI pipeline improves fetal brain ultrasound navigation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new pipeline for fetal brain ultrasound scanning that aims to improve navigation to standard planes. The system uses a semi-supervised segmentation model to estimate plane pose and provide real-time proximity feedback, achieving a mean Intersection over Union of 0.93 for standard planes. This pipeline has been successfully deployed on an NVIDIA Clara AGX device, demonstrating real-time inference speeds of 39 Hz, and has been retrospectively validated on real fetal scan videos. AI

IMPACT This research could lead to more precise and efficient prenatal scanning, aiding medical professionals in diagnosis and monitoring.

RANK_REASON This is a research paper detailing a new AI pipeline for medical imaging. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI pipeline improves fetal brain ultrasound navigation

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This is a research paper detailing a new AI pipeline for medical imaging. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Chiara Di Vece, Antonio Cirigliano, Meala Le Lous, Raffaele Napolitano, Anna L. David, Donald Peebles, Pierre Jannin, Francisco Vasconcelos, Danail Stoyanov ·

    Measuring proximity to standard planes during fetal brain ultrasound scanning

    arXiv:2404.07124v2 Announce Type: replace-cross Abstract: This paper presents a pipeline designed to bring ultrasound (US) plane pose estimation closer to clinical use, demonstrating the feasibility of continuous, real-time proximity feedback for navigation to the standard planes…

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