Christoph Hoeschen

An artifact-free structure-saving noise reduction using the correlation between two images for threshold determination in the wavelet domain

A new method of noise reduction based on shrinkage in the wavelet domain has been created for the application in projection radiography. The method is based on comparing two similar or quasi-identical images of the same object. Using an appropriate measure of similarity, these images are compared with each other in order to produce the weighting matrices. The weighting factors for the wavelet coefficients are chosen to be proportional to the elements of the weighting matrices. One image of the pair is then reconstructed from the weighted wavelet coefficients. The effect of this kind of de-noising is a suppression of those structures in the image which don’t correlate with the structures in the other image of the pair. Normally the suppressed structures are quantum or scatter noise, while the correlated structures which are not affected at all, are the real anatomical structures.

Voxel or MIRD-type model: a sensitivity study relevant to nuclear medicine

Scope of this work is to investigate for which type of radiopharmaceuticals is particularly important to perform patient dosimetry using realistic reference voxel models (a male and a female) instead of the MIRD-type model. For the present work, calculations for patient doses were performed using biokinetic data and the SAFs of the voxel models. A comparison in relation to organ and effective dose estimates by the two methods was done for radiopharmaceuticals chosen for their widely differing biodistributions. By comparing directly the organ doses resulting from the MIRD-type phantom to those from the voxel ones, both types representing the average patient, it can be studied for which types of radiopharmaceuticals a change-over to voxel-based SAFs is essential. Moreover, gender specific differences were studied.

Modeling and testing of a non-standard scanning device with dose reduction potential

A non-standard scanning device with dose-reduction potential was proposed at the SPIE Medical Imaging conference 2006. The new device obtains the Radon data after the X-ray beam is collimated through a special mask. This mask is combined with a new geometry that permits an efficient data collection, thus the device has the potential of reducing the dose by a factor of two. In this work, we report a prototype of the new device and experimental data acquisition using only the mask of the new scanning geometry. In order to obtain the optimal parameters for the scanning device, several factors have been considered, including detector elements and shielding shape, fan beam angle, speed of the source rotation and materials employed. The calibration of the detector elements needs especial attention, due to the dependence of the detector response on the energy of the X-rays. A simplfied version of the device was designed and mounted. Phantom data were acquired using this prototype and were used to test the performance of the new design. The results obtained are highly promising, even though the prototype developed does not make use yet of all the potential features proposed in the theory.

Voxel Phantoms for Internal Dosimetry

The calculation of radiation dose from internally incorporated radionuclides is based on so-called absorbed fractions (AFs) and specific absorbed fractions (SAFs). AFs specify the fraction of energy emitted by radioactivity in a given (source) organ that is absorbed in the source organ itself and in other (target) organs. SAFs are AFs divided by target organ mass.

Separating the uncorrelated noise from the correlated detector noise of flat panel systems in order to quantify flat panel noise easily

One big advantage in terms of image quality of modern flat panel detector systems compared to CR systems beside the better DQE of these systems is the possibility to correct for inhomogeneities of the X-ray beam and the detector (flat field correction) as well as for bad pixels. However, the used correction methods are taking a lot of time or do not cover all possible combinations of radiation quality and exposure used for patient imaging. A method is presented to achieve these correction images very easily by using a proposed method for comparing two images. This method, which has so far been used for certain noise measurements and in some cases noise reduction, can also be used for separating correlated from uncorrelated noise by correlating in frequency sub-bands the information of two images. In this study it is proven, that the uncorrelated noise image of two expositions is very similar to the correction image gained just before the two exposures. That allows to calibrate a detector quite more often and for much more beam qualities/exposures than before to achieve a better correction and another possibility of constancy testing for flat panel detectors, because the proposed method is so sensitive that it will detect single pixel changes within the detector.

Measuring and reconstructing high-resolution high-contrast 3D data of a breast specimen for numerical simulations

For the numerical simulation of the radiation transport in the female breast, it is necessary to generate a numerical model of it. Despite of the success achieved by creating such models, for a more precise numerical dosimetry of the radiation transport and optimization of the imaging process, one needs more detailed numerical models. Unfortunately it is not always possible to appropriately accomplish this task on the base of data available today from conventional tomographic devices. The reason is a low contrast in the reconstructed image. This kind of problem was faced when attempting to segment the glandular and interlobular tissues in the 3D data of a breast specimen reconstructed on the Siemens CT device in the University Hospital in Magdeburg. To solve this problem, we have created a set of different 2D x-ray images of the breast specimen on the digital flat panel detector. The 3D distribution of the absorption function of the specimen was then reconstructed from the grey values of these images.

Reconstruction Algorithms and Scanning Geometries in Tomographic Imaging

In general tomographic imaging consists of two steps: the acquisition of data and the reconstruction. Thereby the following triple problem has to be solved: choose an efficient reconstruction algorithm, identify the optimal sampling conditions imposed on measured data as required by this reconstruction algorithm, and find an efficient way of collecting such data in the practice.

CT with Dual Optimal Reading: compatibility of the two data sets and interpolation issues

The geometry of CT d’Or (Dual Optimal Reading), presented in another abstract for this conference, acquires data for two independent but complementary reconstructions using a special mask to collimate the fan beam. However, 25 % of the pixels in the sinogram must be calculated through interpolation. In this contribution, we explain the structure of the data and thus the need for that interpolation. We compare experimental results of both kind of reconstructions, obtained with a simplified test-device. Additionally, we show the potential of new 2D-interpolation methods within the reconstruction algorithm OPED (Orthogonal Polynomial Expansion on Disc), for which the geometry of CT d’Or is optimally suited.

Radiation Exposure and Protection in Multislice CT

Technical progress in computed tomography (CT) has substantially increased the clinical efficacy of CT procedures and offered promising new applications in diagnostic imaging. On the other hand, data from various national surveys have confirmed, as a general pattern, the growing impact of CT as a major source of patient and population exposure. From a radiation-hygienic point of view, it is thus necessary to optimize the medical benefit of CT examinations to patients, while strictly controlling and reducing their risk from the radiation exposure. It is the purpose of this chapter to summarize relevant dosimetric concepts for dose assessment in CT, to give an overview on the specific factors determining radiation exposure to patients in MSCT, and to provide suggestions for the optimization of MSCT protocols to balance patient exposure against image quality.

Improvement of the OPED algorithm by means of introducing an integration into the evaluation process

The tomographic method based on the orthogonal polynomial expansion on disc (OPED) was presented at SPIE conference of Medical Imaging 2006. We could show already some advantages compared to FBP as it is commonly used in todays CT systems. However, OPED did show for some specific cases some noise in the reconstructed images and even artefacts, mainly an aliasing. We have found that the OPED algorithm can be essentially improved by integrating the polynomial over the whole area belonging to the pixel instead of assigning to the whole pixel the polynomial value calculated just for one point of this pixel (typically bottom left). This advantageous implementation is effective in view of reduction of the aliasing artefacts and noise without affecting the resolution. This can be fulfilled effectively for OPED due to its simple structure.