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Fig. 3 | BMC Medical Imaging

Fig. 3

From: Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection

Fig. 3

A child under the age of 8, 6 h after suffering from traffic accident. The scan voltage was 120 kV, current was 175 mA, CTDI = 17.43 mGy, DLP = 278.88 mGy cm, A–D were 5 mm images and E–H were 0.625 mm images with FBP, 50%ASIR-V, 100%ASIR-V and DL-H, respectively. Hemorrhage and peripheral edema of left temporal were detected (black hollow arrow) and could be seen on all images, 3C and 3D had the lowest image noise. Only thin slice images could show the epidural hemorrhage (black arrow) and hemorrhages in tentorium cerebellum (white arrows), 100%ASIR-V and DL-H could confirm it, but 100%ASIR-V had blurred margins, couldn’t depict the lesion exactly. Only DL-H thin slice image met the diagnostic requirement

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BMC Medical Imaging

ISSN: 1471-2342

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