| Literature DB >> 29994711 |
Abstract
An automatic and objective assessment of image quality is important in an era, where large-scale processing of imaging data from multi-center studies becomes commonplace. Based on a comprehensive statistical image model that includes noise and blur, a measure for image acuity is derived here as the ratio of the maximal gradient magnitude and the intensity difference at a boundary. Acuity may be affected by the object under study, the image acquisition, reconstruction processes, and any post-processing steps. The acuity measure presented here is post-hoc, intuitive to understand, simple to compute, and easily integrates with other standard measures of image quality. Three applications in medical imaging are included where our acuity measure is useful in the objective and automatic assessment of image quality.Mesh:
Year: 2018 PMID: 29994711 DOI: 10.1109/TIP.2018.2851673
Source DB: PubMed Journal: IEEE Trans Image Process ISSN: 1057-7149 Impact factor: 10.856