Application of Artificial Intelligence in Paediatric Imaging
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8441-1_14
Reference47 articles.
1. Sammer MBK, Sher AC, Towbin AJ. Ensuring adequate development and appropriate use of artificial intelligence in pediatric medical imaging. AJR Am J Roentgenol. 2022;218(1):182–3.
2. Kromrey ML, Tamada D, Johno H, et al. Reduction of respiratory motion artifacts in gadoxetate-enhanced MR with a deep learning-based filter using convolutional neural network. Eur Radiol. 2020;30(11):5923–32.
3. Du T, Zhang H, Li Y, et al. Adaptive convolutional neural networks for accelerating magnetic resonance imaging via k-space data interpolation. Med Image Anal. 2021;72:102098.
4. Sun J, Li H, Li J, et al. Improving the image quality of pediatric chest CT angiography with low radiation dose and contrast volume using deep learning image reconstruction. Quant Imaging Med Surg. 2021;11(7):3051–8.
5. Sun J, Li H, Wang B, et al. Application of a deep learning image reconstruction (DLIR) algorithm in head CT imaging for children to improve image quality and lesion detection. BMC Med Imaging. 2021;21(1):108.
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