Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction.

@article{Fletcher2015ObserverPI,
  title={Observer Performance in the Detection and Classification of Malignant Hepatic Nodules and Masses with CT Image-Space Denoising and Iterative Reconstruction.},
  author={Joel G. Fletcher and L Yu and Zhoubo Li and Armando Manduca and Daniel J. Blezek and David M. Hough and Sudhakar K. Venkatesh and Gregory C Brickner and Joseph Cernigliaro and Amy K. Hara and Jeff L. Fidler and David S. Lake and Maria S. Shiung and David P. Lewis and Shuai Leng and Kurt E. Augustine and Rickey E. Carter and David R. Holmes and Cynthia H. McCollough},
  journal={Radiology},
  year={2015},
  volume={276 2},
  pages={465-78}
}
PURPOSE To determine if lower-dose computed tomographic (CT) scans obtained with adaptive image-based noise reduction (adaptive nonlocal means [ANLM]) or iterative reconstruction (sinogram-affirmed iterative reconstruction [SAFIRE]) result in reduced observer performance in the detection of malignant hepatic nodules and masses compared with routine-dose scans obtained with filtered back projection (FBP). MATERIALS AND METHODS This study was approved by the institutional review board and was… CONTINUE READING
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