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Sara Börjesson

Publications and source records attributed to Sara Börjesson.

7 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.

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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.

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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.

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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).

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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.

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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.

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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.

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