3-dimensional adaptive raw-data filter: evaluation in low dose chest multidetector-row computed tomography
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Updated: Jul 19, 2026

Three-Dimensional Reconstruction for the Whole Lung with Early Multiple Pulmonary Nodules
Published on: October 13, 2023
Takeshi Kubo1, Mizuki Nishino, Aya Kino
1Department of Radiology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA. tkubo@bidmc.harvard.edu
Objectives:
To evaluate a 3-dimensional adaptive raw-data filter in reducing streak artifacts in low dose chest computed tomographic (CT) images.
Methods:
Fourteen adult patients who underwent low dose chest CT examination (parameters: 25 or 50 mAs, 120 kV) on 64-detector CTscanner were included in this study. We prepared 2 sets of contiguous 5-mm thick images by reconstruction with and without 3-dimensional adaptive raw-data filter (filter-processed and unprocessed images). Streak artifacts and visualization of peripheral vessels in both filter-processed and unprocessed images were evaluated using a 5-point scale. Upper, middle, and lower thorax were evaluated separately.
Results:
The difference in artifact severity was statistically significant in upper and lower thorax (P = 0.002 and 0.03, respectively), whereas it was not significant in middle thorax (P = 0.13). The difference in the visibility of peripheral pulmonary vessels was not statistically significant in all anatomical regions.
Conclusions:
The 3-dimensional adaptive raw-data filter reduced streak artifacts in low dose chest CT in upper and lower thorax.
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