首页|Capital Medical University Reports Findings in Artificial Intelligence (Accelera ting brain three-dimensional T2 fluid-attenuated inversion recovery using artifi cial intelligence-assisted compressed sensing: a comparison study with parallel ...)
Capital Medical University Reports Findings in Artificial Intelligence (Accelera ting brain three-dimensional T2 fluid-attenuated inversion recovery using artifi cial intelligence-assisted compressed sensing: a comparison study with parallel ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News-New research on Artificial Intelligenc e is the subject of a report. According to newsreporting from Beijing, People's Republic of China, by NewsRx journalists, research stated, "Shorteningthe acqu isition time of brain three-dimensional T2 fluid-attenuated inversion recovery ( 3D T2 FLAIR) byusing acceleration techniques has the potential to reduce motion artifacts in images and facilitate clinicalapplication. This study aimed to as sess the image quality of brain 3D T2 FLAIR accelerated by artificialintelligen ce-assisted compressed sensing (ACS) in comparison to 3D T2 FLAIR accelerated by parallelimaging (PI)."The news correspondents obtained a quote from the research from Capital Medical University, "In thisprospective cohort study, 102 consecutive participants, inc luding both healthy individuals and those withsuspected brain diseases, were re cruited and underwent both ACS- and PI-3D T2 FLAIR scans with a3.0-Tesla magnet ic resonance imaging system from February 2023 to October 2023 in Beijing Tiantan Hospital, Capital Medical University. Quantitative assessment involved white m atter (WM) and graymatter (GM) signal-to-noise ratio (SNR) and contrast-to-nois e ratio (CNR), whole-image sharpness, andtumor volume. Qualitative assessment i ncluded the scoring of overall image quality, GM-WM bordersharpness, and diagno stic confidence in lesion detection. ACS-3D T2 FLAIR exhibited a shorter acquisition time compared to PI-3D T2 FLAIR (105 320 seconds). ACS-3D T2 FLAIR, compare d to PI-3DT2 FLAIR, demonstrated a significantly higher mean SNR (25.922±6.811 22.544±5.853; P<0.001), SNR(18.324±7.137 17.102±6.659; P=0 .049), CNR (4.613±1.547 4.160±1.552; P<0.001), and sharpnes s(0.413±0.049 0.396±0.034; P<0.001), while no significant differences were found for the overall imagequality ratings (P=0.063) or GM-WM border sharpness ratings (P=0.125). A good agreement on tumorvolume was achieve d between ACS-3D T2 FLAIR and PI-3D T2 FLAIR images (intraclass correlationcoef ficient =0.999; 0.998-1.000; P<0.001). Images acquired with ACS demonstrated nearly equivalentdiagnostic confidence to those obtained with PI (P >0.05)."
BeijingPeople's Republic of ChinaAsi aArtificial IntelligenceDiagnostics and ScreeningEmerging TechnologiesHe alth and MedicineMachine Learning
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