ArticleInternational journal of computer assisted radiology and surgery2018
SUPRA: open-source software-defined ultrasound processing for real-time applications : A 2D and 3D pipeline from beamforming to B-mode.
Article in International journal of computer assisted radiology and surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Needle tracking in low-resolution ultrasound volumes using deep learning.International journal of computer assisted radiology and surgery · 2024Article
- Systematic analysis of volumetric ultrasound parameters for markerless 4D motion tracking.International journal of computer assisted radiology and surgery · 2022Article
- Insights into Infusion-Based Targeted Drug Delivery in the Brain: Perspectives, Challenges and Opportunities.International journal of molecular sciences · 2022Review
- Modular robotic platform for precision neurosurgery with a bio-inspired needle: System overview and first in-vivo deployment.PloS one · 2022Article
- An unsupervised learning approach to ultrasound strain elastography with spatio-temporal consistency.Physics in medicine and biology · 2021Article
- A Real-Time, GPU-Based Implementation of Aperture Domain Model Image REconstruction.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2021Article
- Application of machine learning in ophthalmic imaging modalities.Eye and vision (London, England) · 2020Review
- Improved Visualization in Difficult-to-Image Stress Echocardiography Patients Using Real-Time Harmonic Spatial Coherence Imaging.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2019Article
- Article
- Embedded deep learning in ophthalmology: making ophthalmic imaging smarter.Therapeutic advances in ophthalmologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
purposeResearch in ultrasound imaging is limited in reproducibility by two factors: First, many existing ultrasound pipelines are protected by intellectual property, rendering exchange of code difficult. Second, most pipelines are implemented in special hardware, resulting in limited flexibility of implemented processing steps on such platforms.
methodsWith SUPRA, we propose an open-source pipeline for fully software-defined ultrasound processing for real-time applications to alleviate these problems. Covering all steps from beamforming to output of B-mode images, SUPRA can help improve the reproducibility of results and make modifications to the image acquisition mode accessible to the research community. We evaluate the pipeline qualitatively, quantitatively, and regarding its run time.
resultsThe pipeline shows image quality comparable to a clinical system and backed by point spread function measurements a comparable resolution. Including all processing stages of a usual ultrasound pipeline, the run-time analysis shows that it can be executed in 2D and 3D on consumer GPUs in real time.
conclusionsOur software ultrasound pipeline opens up the research in image acquisition. Given access to ultrasound data from early stages (raw channel data, radiofrequency data), it simplifies the development in imaging. Furthermore, it tackles the reproducibility of research results, as code can be shared easily and even be executed without dedicated ultrasound hardware.
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29594853What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.