ArticleIEEE transactions on medical imaging2018
Blind Source Separation-Based Motion Detector for Imaging Super-Paramagnetic Iron Oxide (SPIO) Particles in Magnetomotive Ultrasound Imaging.
Article in IEEE transactions on medical imaging, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Magnetic particles in motion: magneto-motive imaging and sensing.Theranostics · 2022Review
- Single Magnetic Particle Motion in Magnetomotive Ultrasound: An Analytical Model and Experimental Validation.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2021Article
- Inversion of displacement fields to quantify the magnetic particle distribution in homogeneous elastic media from magnetomotive ultrasound.Physics in medicine and biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In magnetomotive ultrasound (MMUS) imaging, an oscillating external magnetic field displaces tissue loaded with super-paramagnetic iron oxide (SPIO) particles. The induced motion is on the nanometer scale, which makes its detection and its isolation from background motion challenging. Previously, a frequency and phase locking (FPL) algorithm was used to suppress background motion by subtracting magnetic field off ( -off) from on ( -on) data. Shortcomings to this approach include long tracking ensembles and the requirement for -off data. In this paper, a novel blind source separation-based FPL (BSS-FPL) algorithm is presented for detecting motion using a shorter ensemble length (EL) than FPL and without -off data. MMUS imaging of two phantoms containing an SPIO-laden cubical inclusion and one control phantom was performed using an open-air MMUS system. When background subtraction was used, contrast and contrast to noise ratio (CNR) were, respectively, 1.20±0.20 and 1.56±0.34 times higher in BSS-FPL as compared to FPL-derived images for EL < 3.5 s. However, contrast and CNR were similar for BSS-FPL and FPL for EL ≥ 3.5 s. When only -on data was used, contrast and CNR were 1.94 ± 0.21 and 1.56 ± 0.28 times higher, respectively, in BSS-FPL as compared to FPL-derived images for all ELs. Percent error in the estimated width and height was 39.30% ± 19.98% and 110.37% ± 6.5% for FPL and was 7.30% ± 7.6% and 16.21% ± 10.29% for BSS-FPL algorithm. This paper is an important step toward translating MMUS imaging to in vivo application, where long tracking ensembles would increase acquisition time and -off data may be misaligned with -on due to physiological motion.
Indexed as
Identifiers
What 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.