研究目的
Discuss techniques for improving the image quality of diagnostic computed tomography and magnetic resonance imaging with the aid of deep learning.
研究成果
Deep learning techniques developed by computer scientists can significantly improve the image quality of CT and MRI studies. These techniques are categorized into noise and artifact reduction, super resolution, and image acquisition and reconstruction, each offering potential benefits such as reduced radiation exposure, shorter scanning times, and improved diagnostic ability. However, the high calculation cost and nonlinear processing nature of deep learning require careful application and additional hardware like GPUs.
研究不足
The paper does not specify technical and application constraints of the experiments or potential areas for optimization.
