Feasibility of Deep Learning Algorithm to Optimize the Noise and Texture of Children's Head CT
10.3969/j.issn.1005-5185.2024.02.017
- VernacularTitle:深度学习迭代重建算法优化儿童头颅CT图像噪声和图像纹理的可行性
- Author:
Hongwei TIAN
1
;
Yun PENG
;
Daoyong LIU
;
Haoyan LI
;
Yong LIU
;
Tianyu HONG
;
Jihang SUN
Author Information
1. 首都医科大学附属北京儿童医院影像中心,北京 100045
- Keywords:
Tomography,X-ray computed;
Head;
Children;
Low-radiation dose;
Deep learning
- From:
Chinese Journal of Medical Imaging
2024;32(2):193-198
- CountryChina
- Language:Chinese
-
Abstract:
Purpose To evaluate the image quality improvement of deep learning iterative reconstruction(DLIR)on pediatric head CT images of head injury and to evaluate the performance of DLIR and conventional adaptive statistical iterative reconstruction-veo(ASIR-V)of noise and image texture of CT image in children's head trauma.Materials and Methods A total of 80 cases in Beijing Children's Hospital,Capital Medical University from December 7th to 11th 2020 of children's head low-dose CT were retrospectively selected.Scan voltage was 120 kV.Scan current was 150-220 mA.The raw data were reconstructed into 5 mm thick slice and 0.625 mm thin slice brain window and bone window images.50%ASIR-V and high weight DLIR images(DL-H)were reconstructed,respectively.A 4-point system was used to subjectively evaluate the display of sulcus,brain matter and bone.The number of lesions in each group was counted.The CT value and image noise values of gray matter and white matter were measured,and the contrast to noise ratio was calculated,then measured the blur metric index was measured in the same slice.The differences between the two image reconstruction methods were compared.Results Compared to 50%ASIR-V images,DL-H significantly improved the display ability of the sulcus and ventricles,as well as the display ability of the brain parenchyma(W=5.5-22.2,all P<0.05)in both slice thickness.There was no statistically significant difference in the display ability of the sulcus and ventricles between 5 mm 50%ASIR-V and 0.625 mm DL-H images(W=0.9,2.0,P=0.32,0.05,respectively).In terms of bone display ability,all images could achieve a maximum score of 4.0.A total of 35 lesions were found in 80 patients via 5 mm 50%ASIR-V and DL-H images,including 12 hemorrhagic lesions,1 intracranial gas,9 fractures,and 13 soft tissue swelling.In terms of objective evaluation,the noise level of DL-H images was significantly lower than that of 50%ASIR-V images(t=21.4-35.7,all P<0.05),and there was no statistically significant difference in noise and contrast noise ratio between 5 mm 50%ASIR-V and 0.625 mm DL-H images(t=1.7-2.2,all P≥0.05).The blur metric index showed that DL-H was superior to 50%ASIR-V images(t=6.1,10.0,both P<0.05),and there was no statistically significant difference in blur metric index between 0.625 mm DL-H and 5 mm 50%ASIR-V images(t=2.6,P=0.28).Conclusion DLIR can improve the CT image quality and image texture of children's head trauma,0.625 mm DL-H image quality is close to 5 mm 50%ASIR-V image,which can meet the diagnostic requirements,and possible to further reduce the radiation dose.
