Purpose: To investigate the accuracy of low signal-to-noise ratio (SNR) T-2 and T-2* measurements using array coils and optimal B-1 image reconstruction (OBR) compared to the standard root sum of squares (RSS) reconstruction. Materials and Methods: Calibrated gels were used for the in vitro study of T-2. T-2 and T-2* measurements were obtained from a volunteer's knee and liver, respectively. T-2 and T-2* measurements were performed using multiecho spin echo and multiecho gradient echo sequences, respectively. SNR was deliberately kept low. The same raw data were used for both reconstructions. For the in vivo studies the effect of signal averaging was also investigated. Results: The optimal reconstructions demonstrated a lower mean background noise level than RSS. In vitro, the T-2 measurements made with OBR images agreed better with a reference high SNR measurement than measurements made from RSS images; the RSS image results overestimated the T2. In vivo, increasing the signal averages decreased the difference between the measurements obtained using the OBR and RSS methods, with RSS resulting in longer relaxation times. Conclusion: This work demonstrates improvements to the accuracy of T-2 and T-2* measurements obtained when OBR is used compared to RSS, particularly in the case of low SNR.
机构:
Beijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R China
Li, Yansong
Zhao, Lulu
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Beijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R China
Zhao, Lulu
Tian, Yun
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Beijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R China
Tian, Yun
Zhao, Shifeng
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Beijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R ChinaBeijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R China
Zhao, Shifeng
STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART. REGULAR AND CMRXRECON CHALLENGE PAPERS, STACOM 2023,
2024,
14507
: 303
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313
机构:
John P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, CanadaJohn P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, Canada
Nikolova, Simona
Sun, Ziqi
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John P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, CanadaJohn P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, Canada
Sun, Ziqi
Bellyou, Miranda
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John P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, CanadaJohn P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, Canada
Bellyou, Miranda
Bartha, Robert
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John P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, Canada
Univ Western Ontario, Dept Diagnost Radiol & Nucl Med, London, ON N6A 5B8, Canada
Univ Western Ontario, Dept Med Biophys & Psychiat, London, ON N6A 5B8, CanadaJohn P Robarts Res Inst, Imaging Res Labs, London, ON N6A 5K8, Canada