Enhancement method that provides direct and independent control of fundamental attributes of image quality for radiographic imagery

An image‐based technique to assess the perceptual quality of clinical chest radiographs

“…Previous studies have suggested that an automated evaluation of image quality may improve the consistency of image quality across imaging systems, [1][2][3][4] provide benchmarks for image processing methods, 5 and provide a convenient way to automatically optimize parameters of image processing algorithms. 6 Such an approach may also enable a reduction of the radiation dose while maintaining acceptable image quality for the purpose of clinical diagnosis. 7,8 Current image quality assessment methods predominantly aim to quantify intrinsic components of image quality, such as modulation transfer function (MTF), noise power spectrum (NPS), and detective quantum efficiency (DQE), for an imaging system with the use of uniform or structurally simple phantoms.…”

Neonatal Chest Computed Radiography: Image Processing and Optimal Image Display

“…The results of this study can be applied to soft-copy and hard-copy interpretation, provided the image-processing parameters are adapted to compensate image appearance for the dynamic range, gray-scale resolution, and spatial resolution differences among printers and soft displays. The concept of the building blocks of image quality has been detailed [17].…”

A GPU-Accelerated Modified Unsharp-Masking Method for High-Frequency Background- Noise Suppression

“…In fact, the mask often contains highfrequency noise components along with edge-information, and thus can lead to noise-amplification. Over the past several years, quite a few UM-inspired techniques [18][19][20][21][22][23][24][25][26][27][28][29][30][31] were reported which have significantly improved the image quality and a few of them further dealt with the noise amplification issue as well.…”