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[Evaluation of Low-contrast Detectability of Different Reconstruction Algorithms and Noise Reduction Intensities in
Haruna Hatakeyama1, Yoshitaka Ota1, Akio Tamura2
1Division of Central Radiology, Iwate Medical University Uchimaru Medical Center.
Purpose:
The effects of reconstruction algorithm and noise reduction intensity on low-contrast detectability in abdominal CT examinations were investigated.
Methods:
FBP, hybrid IR, and deep learning-based reconstruction methods (DLR for body, DLR for body sharp) were compared using an upper abdominal pseudo-human phantom. Imaging was performed under four radiation dose conditions, with three noise reduction intensities, and NPS and CNRLO were used as evaluation indices.
Results:
DLR for body sharp showed excellent low-contrast detection performance with strong noise reduction and achieved a higher CNRLO than the others. Hybrid IR and DLR for body showed equivalent performance regardless of noise reduction intensity, confirming the limitations of low-frequency noise suppression.
Conclusion:
It is important to select a reconstruction algorithm and noise reduction intensity according to the purpose of the examination, and DLR for body sharp is useful for improving image quality and reducing exposure at low doses.
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