The aim of this study was to evaluate the diagnostic potential of virtual endoscopy (VE) and to compare it with axial CT slices, multiplanar reconstructions (MPR), minimal intensity projections (mIP), and bronchoscopy in patients diagnosed with bronchogenic carcinoma. Thirty patients underwent a spiral CT. Axial CT images were transferred to an Onyx workstation (Silicon Graphics, Sun Microsystems, Mountain View, Calif.) for performing virtual endoscopy. Accuracy for this procedure was tested by three radiologists on a monitor in comparison with axial CT slices, MPR, mIP, and bronchoscopy concerning the localization and degree of stenoses. Endoluminal tumors were identified by virtual bronchoscopy with no statistically significant difference of localization or grading of stenosis in comparison with bronchoscopy, axial CT slices, MPR and mIP. Axial CT slices, MPR, and mIP showed poorer results with over- or underestimation of stenoses compared with VE and bronchoscopy. Passing of stenoses was only possible with VE in 5 patients. Virtual endoscopy is a non-invasive method for identification of endoluminal tumors and is comparable to real bronchoscopy.

A complete evaluation strategy had been developed for thoracic X-ray imaging. It has been validated by investigating five chest-radiography systems, two of these systems after optimising image processing. The systems were a screen-film combination, a selenium drum, a conventional and a transparent imaging plate and a Cs/I-based flat panel detector (the two latter ones have been optimised using different post processing). At first all detectors have been characterised using physical parameters like DQE and MTF. After that all systems have been evaluated by human observer studies using anatomy in clinical images (VGA, ICS) and added pathological structures in thoracic phantom images (ROC). The ranking of the image quality of the systems was nearly the same in all studies. There was a similar assessment of main image quality parameters like spatial resolution, dynamic range and MTF. The modification of image post processing changed the visibility of pathological structures more than the visualisation of the anatomical criteria. The assessment of the clinical image quality has to be done for anatomical structures, and the recognition of pathological structures has to be evaluated.

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The purpose of this study was to evaluate the diagnostic performance of an additional stationary anti-scatter grid in digital selenium radiography (DSR) compared with images acquired with only an air gap. Chest radiographs were obtained with DSR in 100 patients with and without an anti-scatter grid. Four observers scored 12 anatomical landmarks, catheters and wire cerclages for their visualization in both subsets of images. Statistical analysis was performed using a paired t-test. Anatomical landmarks, catheters and wire cerclages were statistically better visualized in regions of high attenuation when the images were performed with an anti-scatter grid. No statistically significant difference was noted for peripheral regions, nor for sex and weight of the patient between the two modalities. Therefore, an anti-scatter grid is not recommended for chest radiography as it increases the radiation exposure of patients without having a significant impact on visualization for all regions of the chest.

There are many aspects that influence and deteriorate the detection of pathologies in X-ray images. Some of those are due to effects taking place in the stage of forming the X-ray intensity pattern in front of the x-ray detector. These can be described as motion blurring, depth blurring, anatomical background, scatter noise and structural noise. Structural noise results from an overlapping of fine irrelevant anatomical structures. A method for measuring the combined effect of structural noise and scatter noise was developed and will be presented in this paper. This method is based on the consideration that within a pair of projections created after rotation of the object with a small angle (which is within the typical uncertainty in positioning the patient) both images would show the same relevant structures whereas the projection of the fine overlapping structures will appear quite differently in the two images. To demonstrate the method two X-ray radiographs of a lung phantom were produced. The second radiograph was achieved after rotating the lung by an angle of about 3°. Dyadic wavelet representations of both images were regarded. For each value of the wavelet scale parameter the corresponding pair of approximations was matched using the cross correlation matching technique. The homologous regions of approximations were extracted. The image containing only those structures that appear in both images simultaneously was then reconstructed from the wavelet coefficients corresponding to the homologous regions. The difference between one of the original images and the noise-reduced image contains the structural noise and the scatter noise.