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Markus Håkansson

Publications and source records attributed to Markus Håkansson.

13 recordsLinked to original sources

Nodule detection in digital chest radiography: part of image background acting as pure noise.

There are several factors that influence the radiologist's ability to detect a specific structure/lesion in a radiograph. Three factors that are commonly known to be of major importance are the signal itself, the system noise and the projected anatomy. The aim of this study was to determine to what extent the image background acts as pure noise for the detection of subtle lung nodules in five different regions of the chest. A receiver operating characteristic (ROC) study with five observers was conducted on two different sets of images, clinical chest X-ray images and images with a similar power spectrum as the clinical images but with a random phase spectrum, resulting in an image background containing pure noise. Simulated designer nodules with a full-width-at-fifth-maximum of 10 mm but with varying contrasts were added to the images. As a measure of the part of the image background that acts as pure noise, the ratio between the contrast needed to obtain an area under the ROC curve of 0.80 in the clinical images to that in the random-phase images was used. The ratio ranged from 0.40 (in the lateral pulmonary regions) to 0.83 (in the hilar regions) indicating that there was a large difference between different regions regarding to what extent the image background acted as pure noise; and that in the hilar regions the image background almost completely acted as pure noise for the detection of 10 mm nodules.

Artifacts↗

Nodule detection in digital chest radiography: effect of nodule location.

Most detection studies in chest radiography treat the entire chest image as a single background or divided into the two regions parenchyma and mediastinum. However, the different parts of the lung show great variations in attenuation and structure, leading to different amounts of quantum noise and scattered radiation as well as different complexity. Detailed data on the difference in detectability in the different regions are of importance. The purpose of this study was to quantify the difference in detectability between different regions of a chest image. The chest X ray was divided into six different regions, where each region was considered to be uniform in terms of detectability. Thirty clinical chest images were collected and divided into the different regions. Simulated designer nodules with a full-width-at-fifth-maximum of 10 mm but with varying contrast were added to the images. An equal number of images lacking pathology were included and a receiver operating characteristic (ROC) study was conducted with five observers. Results show that the image contrast needed to obtain a constant value of A(z) (area under an ROC curve) differs by more than a factor of four between different regions.

Artifacts↗

Nodule detection in digital chest radiography: effect of system noise.

Apart from the image content that is the reproduction of anatomy and possible lesions, an X-ray image also contains system noise due to the limited number of photons and other internal noise sources in the system (image plate artefacts, electronic noise, etc.). The aim of this study was to determine the extent to which the system noise influences the detection of subtle lung nodules in five different regions of the chest. This was done by conducting a receiver operating characteristic (ROC) study with five observers on two different sets of images; clinical chest X-ray images and images of a LucAl phantom at similar dose levels found in the different regions of the chest. In both image types, mathematically simulated nodules (with a full-width-at-fifth-maximum of 10 mm) were added to the images at varying contrast levels. As a measure of the influence of system noise on the detection of subtle lung nodules, the ratio between the contrast needed to obtain an area under the ROC curve of 0.80 in the system noise images to that needed in the clinical images was used. The contrast ratio between system noise images and clinical images ranged from approximately 0.02 (in the hilar region) to 0.18 (in the lower mediastinal region). The maximum difference in contrast needed for the corresponding system noise images, collected at the lowest and the highest dose represented in the anatomical image, was a factor of 2. These results indicate that probably no region in a chest X-ray image is limited by the number of quanta to the detector for the detection of 10 mm lung nodules when a radiation dose corresponding to a system with speed class 200 (leading to a detector dose of approximately 9 muGy behind the parenchyma) is used.

Artifacts↗

Nodule detection in digital chest radiography: effect of anatomical noise.

The image background resulting from imaged anatomy can be divided into those components that are meaningful to the observers, in the sense that they are recognised as separate structures, and those that are not. These latter components (reffered to as anatomical noise) can be removed using a method developed within the RADIUS group. The aim of the present study was to investigate whether the removal of the anatomical noise results in images where lung nodules with lower contrast can be detected. A receiver operating characteristic (ROC) study was therefore conducted using two types of images: clinical chest images and chest images in which the anatomical noise had been removed. Simulated designer nodules with a full-width-at-fifth-maximum of 10 mm but with varying contrast were added to the images. The contrast needed to obtain an area under the ROC curve of 0.80, C0.8, was used as a measure of detectability (a low value of C0.8 represents a high detectability). Five regions of the chest X ray were investigated and it was found that in all regions the removal of anatomical noise led to images with lower C0.8 than the original images. On average, C0.8 was 20% higher in the original images, ranging from 7% (the lateral pulmonary regions) to 41% (the upper mediastinal regions).

Artifacts↗

Inter-observer variation in masked and unmasked images for quality evaluation of clinical radiographs.

PURPOSE: To investigate the influence of masking on the inter-observer variation in image quality evaluation of clinical radiographs of chest and lumbar spine. BACKGROUND: Inter-observer variation is a big problem in image quality evaluation since this variation is often much bigger than the variation in image quality between, for example, two radiographic systems. In this study, we have evaluated the effect of masking on the inter-observer variation. The idea of the masking was to force every observer to view exactly the same part of the image and to avoid the effect of the overall 'first impression' of the image. A discussion with a group of European expert radiologists before the study indicated that masking might be a good way to reduce the inter-observer variation. METHODS: Five chest and five lumbar spine radiographs were collected together with detailed information regarding exposure conditions. The radiographs were digitised with a high-performance scanner and five different manipulations were performed, simulating five different exposure conditions. The contrast, noise and spatial resolution were manipulated by this method. The images were printed onto the film and the individual masks were produced for each film, showing only the parts of the images that were necessary for the image quality evaluation. The quality of the images was evaluated on ordinary viewing boxes by a large group of experienced radiologists. The images were examined with and without the masks with a set of image criteria (if fulfilled, 1 point; and not fulfilled, 0 point), and the mean score was calculated for each simulated exposure condition. RESULTS: The results of this study indicate that-contrary to what was supposed-the inter-observer variation increased when the images were masked. In some cases, especially for chest, this increase was statistically significant. CONCLUSIONS: Based on the results of this study, image masking in studies of fulfilment of image criteria cannot be recommended.

Computers↗

An optimisation strategy in a digital environment applied to neonatal chest imaging.

The aim of this study was to find the optimum tube voltage for neonatal chest imaging in computed radiography. The study was designed to take full advantage of the benefits of digital imaging, for example, by comparing the tube voltages at constant effective dose. A phantom study using a living rabbit was first conducted. Images were collected at tube voltages ranging from 40 to 90 kV(p). The reproduction of four structures (central vessels, peripheral vessels, carina and thoracic vertebrae) was rated by 10 radiologists. The reproduction of both central and peripheral vessels was relatively independent of tube voltage. The carina was better reproduced at higher tube voltages whereas the opposite was true for the thoracic vertebrae. Based on the higher importance of the reproduction of the carina it was decided that 90 kV(p) was the optimal tube voltage. To validate the result from the phantom study, a follow-up study was conducted in which images of neonates collected at the tube voltage regularly used at Sahlgrenska University Hospital (70 kV(p)) were compared with images collected at the tube voltage proposed by the phantom study. The follow-up study confirmed the results from the phantom study that the reproduction of the carina was better at 90 than at 70 kV(p). In conclusion, for neonatal chest imaging-given the same effective dose-90 kVp gives better reproduction of important structures than the regularly used 70 kV(p).

Animals↗

Method of simulating dose reduction for digital radiographic systems.

The optimisation of image quality vs. radiation dose is an important task in medical imaging. To obtain maximum validity of the optimisation, it must be based on clinical images. Images at different dose levels can then either be obtained by collecting patient images at the different dose levels sought to investigate-including additional exposures and permission from an ethical committee-or by manipulating images to simulate different dose levels. The aim of the present work was to develop a method of simulating dose reduction for digital radiographic systems. The method uses information about the detective quantum efficiency and noise power spectrum at the original and simulated dose levels to create an image containing filtered noise. When added to the original image this results in an image with noise which, in terms of frequency content, agrees with the noise present in an image collected at the simulated dose level. To increase the validity, the method takes local dose variations in the original image into account. The method was tested on a computed radiography system and was shown to produce images with noise behaviour similar to that of images actually collected at the simulated dose levels. The method can, therefore, be used to modify an image collected at one dose level so that it simulates an image of the same object collected at any lower dose level.

Algorithms↗

A software tool for increased efficiency in observer performance studies in radiology.

Observer performance studies are time-consuming tasks, both for the participating observers and for the scientists collecting and analysing the data. A possible way to optimise such studies is to perform them in a completely digital environment. A software tool-ViewDEX (Viewer for Digital Evaluation of X-ray images)-has been developed in Java, enabling it to function on almost any computer. ViewDEX is designed to handle several types of studies, such as visual grading analysis (VGA), image criteria scoring (ICS) and receiver operating characteristics (ROC). The results from each observer are saved in a log file, which can be exported for further analysis in, for example, a special software for analysing ROC results. By using ViewDEX for an ROC experiment, an evaluation rate of approximately 200 images per hour can be achieved, compared to approximately 25 images per hour using hard copy evaluation. The results are obtained within minutes of completion of the viewing. The risk of human errors in the process of data collection and analysis is also minimised. The viewer has been used in a major trial containing approximately 2700 images.

Computer Simulation↗

Evaluation of image quality of lumbar spine images: a comparison between FFE and VGA.

PURPOSE: The aim of the present study is to compare two different methods for evaluation of the quality of clinical X-ray images. METHODS: Based on fifteen lumbar spine radiographs, two new sets of images were created. A hybrid image set was created by adding two distributions of artificial lesions to each original image. The image quality parameters spatial resolution and noise were manipulated and a total of 210 hybrid images were created. A set of 105 disease-free images was created by applying the same combinations of spatial resolution and noise to the original images. The hybrid images were evaluated with the free-response forced error experiment (FFE) and the normal images with visual grading analysis (VGA) by nine experienced radiologists. RESULTS: In the VGA study, images with low noise were preferred over images with higher noise levels. The alteration of the MTF had a limited influence on the VGA score. For the FFE study, the visibility of the lesions was independent of the sharpness and the noise level. No correlation was found between the two image quality measures. CONCLUSIONS: FFE is a precise method for evaluation of image quality, but the results are only valid for the type of lesion used in the study, whereas VGA is a more general method for clinical image quality assessment. The results of the FFE study indicate that there might be a potential to lower the dose levels in lumbar spine radiography without losing important diagnostic information.

Calibration↗

A conceptual optimisation strategy for radiography in a digital environment.

Using a completely digital environment for the entire imaging process leads to new possibilities for optimisation of radiography since many restrictions of screen/film systems, such as the small dynamic range and the lack of possibilities for image processing, do not apply any longer. However, at the same time these new possibilities lead to a more complicated optimisation process, since more freedom is given to alter parameters. This paper focuses on describing an optimisation strategy that concentrates on taking advantage of the conceptual differences between digital systems and screen/film systems. The strategy can be summarised as: (a) always include the anatomical background during the optimisation, (b) perform all comparisons at a constant effective dose and (c) separate the image display stage from the image collection stage. A three-step process is proposed where the optimal setting of the technique parameters is determined at first, followed by an optimisation of the image processing. In the final step the optimal dose level-given the optimal settings of the image collection and image display stages-is determined.

Computers↗

Nodule detection in digital chest radiography: summary of the RADIUS chest trial.

As a part of the Europe-wide research project 'Unification of physical and clinical requirements for medical X-ray imaging'-governed by the Radiological Imaging Unification Strategies (RADIUS) Group-a major image quality trial was conducted by members of the group. The RADIUS chest trial aimed at thoroughly examining various aspects of nodule detection in digital chest radiography, such as the effects of nodule location, system noise, anatomical noise, and anatomical background. The main findings of the RADIUS chest trial concerning the detection of a lung nodule with a size in the order of 10 mm can be summarised as: (1) the detectability of the nodule is largely dependent on its location in the chest, (2) the system noise has a minor impact on the detectability at the dose levels used today, (3) the disturbance of the anatomical noise is larger than that of the system noise but smaller than that of the anatomical background and (4) the anatomical background acts as noise to a large extent and is the major image component affecting the detectability of the nodule.

Artifacts↗

Nodule detection in digital chest radiography: introduction to the RADIUS chest trial.

Most digital radiographic systems of today have wide latitude and are hence able to provide images with a small constraint on dose level. This opens up for an unprejudiced dose optimisation. However, in order to succeed in the optimisation task, good knowledge of the imaging and detection processes is needed. As a part of the European-wide research project 'unification of physical and clinical requirements for medical X-ray imaging'-governed by the Radiological Imaging Unification Strategies (RADIUS) Group-a major image quality trial was conducted by members of the group. The RADIUS chest trial was focused on the detection of lung nodules in digital chest radiography with the aims of determining to what extent (1) the detection of a nodule is dependent on its location, (2) the system noise disturbs the detection of lung nodules, (3) the anatomical noise disturbs the detection of lung nodules and (4) the image background and anatomical background act as pure noise for the detection of lung nodules. The purpose of the present paper is to give an introduction to the trial and describe the framework and set-up of the investigation.

Artifacts↗

Determination of the two-dimensional detective quantum efficiency of a computed radiography system.

Based on a recently described method for determining the two-dimensional presampling modulation transfer function (MTF), the aperture mask method, a method for determining the two-dimensional detective quantum efficiency (DQE) of a digital radiographic system was developed. The method was applied to a new computed radiography (CR) system and comparisons with one-dimensional determinations of the presampling MTF and the DQE were performed. The aperture mask method was shown to agree with the conventional tilted slit method for determining the presampling MTF along the axes. For the particular CR system studied, the mean of one-dimensional determinations of the DQE in orthogonal directions led to a representative measure of the average DQE behavior of the system up to the Nyquist frequency along the axes, but a deviation was observed above this frequency. In conclusion, the method developed for determining the two-dimensional DQE can be used to determine the imaging properties of a digital radiographic detector system over almost the entire frequency domain, the exception being the lowest frequencies (< or = 0.1 mm(-1)) at which the validity and the reliability of the method are low.

Algorithms↗