Application value of iMAR algorithm in reducing metal artifacts from abdominal implants

Application value of iMAR algorithm in reducing metal artifacts from abdominal implants

Blog Article

Objective: To explore application value of iterative metal artifact reduction (iMAR) algorithm in reducing the artifacts from abdominal metal implants.Methods: The CT images of 32 patients with abdominal metal implants were reconstructed with both iMAR and filtered back projection (FBP) algorithm, respectively.Subjective image quality was assessed by two independent radiologists.Objective image quality indic including signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index (AI) were calculated by the noise values measured at the iphone 14 price arizona most severe level of artifacts near metal implants on images of both iMAR and FBP algorithms.Difference in subjective and objective image quality assessment between iMAR and FBP algorithms was compared.

Results: The overall subjective quality score of iMAR images was significantly higher than FBP images (3.656±0.475 vs.2.156±0.

618, P<0.050).Both SNR and CNR of iMAR image were significantly higher than campicon.com those of FBP images(SNR: 1.890±1.864 vs.

0.720±1.384, P=0.002; CNR: 35.872±13.

154 vs.15.245±12.362, P<0.050, respectively).

AI of iMAR images was significantly lower than that of FBP images (32.690±15.694 vs.152.594±117.

203, P<0.050).Conclusions: iMAR can significantly decrease the metal artifacts and improve the image quality in clinical practice.