On The Application Of Log Compression and Enhanced Denoising In Contrast Enhancement Of Digital Radiography Images

Digital radiography (DR) is becoming popular for the point of care imaging in the recent past. To reduce the radiation exposure, controlled radiation based on as low as reasonably achievable (ALARA) principle is employed and this results in low contrast images. To address this issue, post-processing algorithms such as the Multiscale Image Contrast Amplification (MUSICA) algorithm can be used to enhance the contrast of DR images even with a low radiation dose. In this study, a modification of the MUSICA algorithm is investigated to determine the potential for further contrast improvement specifically for DR images. The conclusion is that combining log compression and its inverse at the appropriate stage with a multi-stage MUSICA and denoising is very promising. The proposed method resulted in an average of 66.5 % increase in the mean contrast-to-noise ratio (CNR) for the test images considered.Comment: 4 pages, 4 figure

Digital chest radiography: an update on modern technology, dose containment and control of image quality

The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems

Suppression of the contrast of ribs in chest radiographs by means of massive training artificial neural network

ABSTRACT We developed a method for suppression of the contrast of ribs in chest radiographs by means of a massive training artificial neural network (MTANN). The MTANN is a trainable highly nonlinear filter that can be trained by using input chest radiographs and the corresponding teacher images. We used either the soft-tissue image or the bone image obtained by use of a dual-energy subtraction technique as the teacher image for suppression of ribs in chest radiographs. When the soft-tissue images were used as the teacher images, the MTANN directly produced a "soft-tissue-image-like" image where the contrast of ribs was suppressed. When the bone images were used as the teacher images, the MTANN was able to produce a "bone-image-like" image, and then was subtracted from the corresponding chest radiograph to produce a bone-subtracted image where ribs are suppressed. Thus, the two kinds of rib-suppressed images, i.e., the soft-tissue-image-like image and the bone-subtracted image, could be produced by use of the MTANNs trained with two different teacher images. We applied each of the two trained MTANNs to non-training chest radiographs to investigate the difference between the processed images. The results showed that the contrast of ribs in chest radiographs almost disappeared, and was reduced to less than 10% in both processed images. The contrast of ribs was reduced slightly better in the soft-tissue-image-like images than in the bone-subtracted images, whereas soft-tissue opacities such as lung vessels and nodules were maintained better in the bone-subtracted images. Therefore, the use of the bone images as the teacher images for training the MTANN has produced better rib-suppressed images where soft-tissue opacities were substantially maintained. A method for rib suppression using the MTANN would be useful for radiologists as well as CAD schemes in detection of lung diseases such as nodules in chest radiographs

Optimisation of the digital radiographic imaging of suspected non-accidental injury.

Aim: To optimise the digital (radiographic) imaging of children presenting with suspected non-accidental injury (NAI).;Objectives: (i) To evaluate existing radiographic quality criteria, and to develop a more suitable system if these are found to be inapplicable to skeletal surveys obtained in suspected NAI. (ii) To document differences in image quality between conventional film-screen and the recently installed Fuji5000R computed radiography (CR) system at Great Ormond Street Hospital for Children, (iii) To document the extent of variability in the standard of skeletal surveys obtained in the UK for suspected NAI. (iv) To determine those radiographic parameters which yield the highest diagnostic accuracy, while still maintaining acceptable radiation dose to the child, (v) To determine how varying degrees of edge-enhancement affect diagnostic accuracy. (vi) To establish the accuracy of soft compared to hard copy interpretation of images in suspected NAI.;Materials and Methods: (i) and (ii) Retrospective analysis of 286 paediatric lateral spine radiographs by two observers based on the Commission of European Communities (CEC) quality criteria, (iii) Review of the skeletal surveys of 50 consecutive infants referred from hospitals throughout the United Kingdom (UK) with suspected NAI. (iv) Phantom studies. Leeds TO. 10 and TO. 16 test objects were used to compare the relationship between film density, exposure parameters and visualisation of object details, (iv) Clinical study. Anteroposterior and lateral post mortem skull radiographs of six consecutive infants were obtained at various exposures. Six observers independently scored the images based on visualisation of five criteria, (v) and (vi) A study of diagnostic accuracy in which six observers independently interpreted 50 radiographs from printed copies (with varying degrees of edge-enhancement) and from a monitor.;Results: The CEC criteria are useful for optimisation of imaging parameters and allow the detection of differences in quality of film-screen and digital images. There is much variability in the quality and number of radiographs performed as part of skeletal surveys in the UK for suspected NAI. The Leeds test objects are either not sensitive enough (TO. 10) or perhaps over sensitive (TO. 16) for the purposes of this project. Furthermore, the minimum spatial resolution required for digital imaging in NAI has not been established. Therefore the objective interpretation of phantom studies is difficult. There is scope for reduction of radiation dose to children with no effect on image quality. Diagnostic accuracy (fracture detection) in suspected NAI is generally low, and is not affected by image display modality.;Conclusions: The CEC quality criteria are not applicable to the assessment of clinical image quality. A national protocol for skeletal surveys in NAI is required. Dedicated training, close supervision, collaboration and consistent exposure of radiologists to cases of NAI should improve diagnostic accuracy. The potential exists for dose reduction when performing skeletal surveys in children and infants with suspected NAI. Future studies should address this issue

Evaluation of a Multi-Scale Enhancement Protocol for Digital Mammography

We have carried out a receiver operating characteristics (ROC) study for the enhancement of mammographic features in digitized mammograms. The study evaluated the benefits of multi-scale enhancement methods in terms of diagnostic performance of radiologists. The enhancement protocol relied on multi-scale expansions and non-linear enhancement functions. Dyadic spline wavelet functions (first derivative of a cubic spline) were used together with a sigmoidal non-linear enhancement function. We designed a computer interface on a softcopy display and performed an ROC study with three radiologists, who specialized in mammography. Clinical cases were obtained from a national mammography database of digitized radiographs prepared by the University of South Florida (USF) and Harvard Medical School. Our study focused on dense mammograms, i.e. mammograms of density 3 and 4 on the American College of Radiology (ACR) breast density rating, which are the most difficult cases in screening, were selected. To compare the performance of radiologists with and without using multi-scale enhancement, two groups of 30 cases each were diagnosed. Each group contained 15 cases of cancerous and 15 cases of normal mammograms. Conventional ROC analysis was applied, and the resulting ROC curves indicated improved diagnostic performance when radiologists used multi-scale non-linear enhancement

Evaluation of a multi-scale enhancement protocol for digital mammography

We have carried out a receiver operating characteristics (ROC) study for the enhancement of mammographic features in digitized mammograms. The study evaluated the benefits of multi-scale enhancement methods in terms of diagnostic performance of radiologists. The enhancement protocol relied on multi-scale expansions and non-linear enhancement functions. Dyadic spline wavelet functions were used together with a sigmoidal non-linear enhancement function. We designed a computer interface ona softcopy display and performed an ROC study with three radiologists, who specialized in mammography. Clinical cases were obtained from a national mammography database of digitized radiographs prepared by the University of South Florida and Harvard Medical School. Our study focused on dense mammograms, i.e. mammograms of density 3 and 4 on the American College of Radiology breast density rating, which are the most difficult cases in screening, were selected. To compare the performance of radiologists with an without using multi-scale enhancement, two groups of 30 cases each were diagnosed. Each group contained 15 cases of cancerous and 15 cases of normal mammograms. Conventional ROC analysis was applied, and the resulting ROC curves indicated improved diagnostic performance when radiologists used multi-scale non-linear enhancement