In this paper, we investigate the effect of the use of wavelet transform for image processing on radiation dose reduction
in computed radiography (CR), by measuring various physical characteristics of the wavelet-transformed images.
Moreover, we propose a wavelet-based method for offering a possibility to reduce radiation dose while maintaining a
clinically acceptable image quality. The proposed method integrates the advantages of a previously proposed technique,
i.e., sigmoid-type transfer curve for wavelet coefficient weighting adjustment technique, as well as a wavelet soft-thresholding
technique. The former can improve contrast and spatial resolution of CR images, the latter is able to
improve the performance of image noise. In the investigation of physical characteristics, modulation transfer function,
noise power spectrum, and contrast-to-noise ratio of CR images processed by the proposed method and other different
methods were measured and compared. Furthermore, visual evaluation was performed using Scheffe's pair comparison
method. Experimental results showed that the proposed method could improve overall image quality as compared to
other methods. Our visual evaluation showed that an approximately 40% reduction in exposure dose might be achieved
in hip joint radiography by using the proposed method.
This paper presents an information-entropy based metric for combined evaluation of resolution and noise properties of
radiological images. The metric is expressed by the amount of transmitted information (TI). It is a measure of how much
information that one image contains about an object or an input. Merits of the proposed method are its simplicity of
computation and the experimented setup. A computer-simulated step wedge was used for simulation study on the
relationship of TI and the degree of blur as well as the noise. Three acrylic step wedges were also manufactured and used
as test sample objects for experiments. Two imaging plates for computed radiography were employed as information
detectors to record X-ray intensities. We investigated the effects of noise and resolution degradation on the amount of TI
by varying exposure levels. Simulation and experimental results show that the TI value varies when the noise level or the
degree of blur is changed. To validate the reasoning and usefulness of the proposed metric, we also calculated and
compared the modulation transfer functions and noise power spectra for the employed imaging plates. Results show that
the TI has close correlation with both image noise and image blurring, and it may offer the potential to become a simple
and generally applicable measure for quality evaluation of medical images.