Comparison of image quality evaluation methods for magnetic resonance imaging using compressed sensing-sensitivity encoding (CS-SENSE)
- PMID: 40353935
- DOI: 10.1007/s12194-025-00911-4
Comparison of image quality evaluation methods for magnetic resonance imaging using compressed sensing-sensitivity encoding (CS-SENSE)
Abstract
This study aimed to compare the relationship between the quantitative values and visual score of acquired images using the CS-SENSE method. T1-weighted image (T1WI) and T2-weighted image (T2WI) were acquired using a phantom created by a 3D printer. Each quantitative values (signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], structural similarity [SSIM], and scale-invariant feature transform [SIFT]) and visual evaluation score (VES) were calculated by the acquired images. The correlation coefficients among the calculating quantitative values and VES were calculated. The difference in methods for evaluating the image quality of T1WI and T2WI images using CS-SENSE was clarified. Variations in image quality, as reflected by VES in T1WI and T2WI images obtained via the CS-SENSE method, can be quantitatively assessed. Specifically, CNR is effective for evaluating changes in T1WI, while SNR, CNR, and SIFT are suitable for assessing variations in T2WI.
Keywords: CS-SENSE; Compressed sensing; Scale-invariant feature transform (SIFT); Sensing–sensitivity encoding (SENSE); Structural similarity (SSIM).
© 2025. The Author(s), under exclusive licence to Japanese Society of Radiological Technology and Japan Society of Medical Physics.
Conflict of interest statement
Declarations. Conflict of interest: The authors declare that they have no conflicts of interest. Ethical approval: All procedures performed in studies involving human participants were in accordance with the ethical standards of the Institutional Review Board (IRB) and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
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