Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

The shape, structure and connectivity of nerve cells are important aspects of neuronal function. Genetic and epigenetic factors that alter neuronal morphology or synaptic localization of pre- and post-synaptic proteins contribute significantly to neuronal output and may underlie clinical states. To assess the impact of individual genes and disease-causing mutations on neuronal morphology, reliable methods are needed. Unfortunately, manual analysis of immuno-fluorescence images of neurons to quantify neuronal shape and synapse number, size and distribution is labor-intensive, time-consuming and subject to human bias and error. We have developed an automated image analysis routine using steerable filters and deconvolutions to automatically analyze dendrite and synapse characteristics in immuno-fluorescence images. Our approach reports dendrite morphology, synapse size and number but also synaptic vesicle density and synaptic accumulation of proteins as a function of distance from the soma as consistent as expert observers while reducing analysis time considerably. In addition, the routine can be used to detect and quantify a wide range of neuronal organelles and is capable of batch analysis of a large number of images enabling high-throughput analysis.

The new artifact suppression design is efficient, for instance, in terms of preserving spatial resolution, as it is applied directly to original raw data. It successfully reduced artifacts in CT images of five patients and in phantom images. Sophisticated interpolation methods are needed to obtain reliable HU values close to the prosthesis.

This study aimed at assessment of efficacy of selective in-plane shielding in adults by quantitative evaluation of the achieved dose reduction and image quality. Commercially available accessories for in-plane shielding of the eye lens, thyroid and breast, and an anthropomorphic phantom were used for the evaluation of absorbed dose and image quality. Organ dose and total energy imparted were assessed by means of a Monte Carlo technique taking into account tube voltage, tube current, and scanner type. Image quality was quantified as noise in soft tissue. Application of the lens shield reduced dose to the lens by 27% and to the brain by 1%. The thyroid shield reduced thyroid dose by 26%; the breast shield reduced dose to the breasts by 30% and to the lungs by 15%. Total energy imparted (unshielded/shielded) was 88/86 mJ for computed tomography (CT) brain, 64/60 mJ for CT cervical spine, and 289/260 mJ for CT chest scanning. An increase in image noise could be observed in the ranges were bismuth shielding was applied. The observed reduction of organ dose and total energy imparted could be achieved more efficiently by a reduction of tube current. The application of in-plane selective shielding is therefore discouraged.

Our objective in this study was to investigate the usefulness of an anti-scatter grid in digital mammography using a contrast detail phantom. The mammography system we investigated was a GE Senographe 2000D. We carried out phantom measurements under various conditions with and without using the anti-scatter grid. A new version of the CDMAM phantom (version 3.4) was used. This phantom consists of a matrix of square cells with disks of varying size and contrast. For given exposure conditions detectability of these disks can be determined and used for construction of contrast detail curves. Previously, a computer program was developed at our institute that performs a fully automatic analysis of the phantom recordings using the ideal observer model. Breast thickness was simulated by a homogeneous layer of PMMA in the range of 1 to 7 cm. Series of images were recorded for different KeV and target-filter combinations depending on the simulated thickness. The dose was kept constant for each thickness with and without using a grid. It appeared that image quality improved for simulated breast thickness below 5 cm when the grid was removed. In the range from 5 to 7 cm contrast detail curves obtained with or without a grid were similar. Results suggest that for compressed breast thickness in the range of 1 to 7 cm a grid might not be needed in the digital mammography system we investigated. Below 5 cm, omitting the grid may allow lower dose to the patient without losing image quality.