Automatic evaluation of the image quality of a mammographic phantom

Automated image quality assessment of mammography phantoms: a systematic review

BACKGROUND

Computerized image analysis is a viable technique for evaluating image quality as a complement to human observers.

PURPOSE

To systematically review the image analysis software used in the assessment of 2D image quality using mammography phantoms.

MATERIAL AND METHODS

A systematic search of multiple databases was performed from inception to July 2020 for articles that incorporated computerized analysis of 2D images of physical mammography phantoms to determine image quality.

RESULTS

A total of 26 studies were included, 12 were carried out using direct digital imaging and 14 using screen film mammography. The ACR phantom (model-156) was the most frequently evaluated phantom, possibly due to the lack of accepted standard software. In comparison to the inter-observer variations, the computerized image analysis was more consistent in scoring test objects. The template matching method was found to be one of the most reliable algorithms, especially for high-contrast test objects, while several algorithms found low-contrast test objects to be harder to distinguish due to the smaller contrast variations between test objects and their backgrounds. This was particularly true for small object sizes.

CONCLUSION

Image analysis software was in agreement with human observers but demonstrated higher consistency and reproducibility of quality evaluation. Additionally, using computerized analysis, several quantitative metrics such as contrast-to-noise ratio (CNR) and the signal-to-noise ratio (SNR) could be used to complement the conventional scoring method. Implementing a computerized approach for monitoring image quality over time would be crucial to detect any deteriorating mammography system before clinical images are impacted.

Analysis of image quality parameter of conventional and dental radiographic digital images

The image quality obtained by a radiographic equipment is very useful to characterize the physical properties of the image radiographic chain, in a quality control of the radiographic equipment. In the radiographic technique it is necessary that the evaluation of the image can guarantee the constancy of its quality to carry out a suitable diagnosis. In this work we have designed some radiographic phantoms for different radiographic digital devices, as dental, conventional, equipments with computed radiography (phosphor plate) and direct radiography (sensor) technology. Additionally, we have developed a software to analyse the image obtained by the radiographic equipment with digital processing techniques, as edge detector, morphological operators, statistical test for the detected combinations‥ The design of these phantoms let the evaluation of a wide range of operating conditions of voltage, current and time of the digital equipments. Moreover, the image quality analysis by the automatic software, let study it with objective parameters.

Analysis of digital image quality indexes for CIRS SP01 and CDMAM 3.4 mammographic phantoms

Mammographic phantom images are usually used to study the quality of images obtained by determined mammographic equipment. The digital image treatment techniques allow carrying out an automatic analysis of the phantom image. Nowadays, the digital radiographic equipments are replacing the traditional film-screen equipments and it is necessary to update the parameters to guarantee the quality of the process. In this work we apply some techniques of digital image processing to compute a specific image quality indexes for mammographic phantoms, namely CIRS SP01 and CDMAM 3.4. to study the evolution of this parameter with different varying conditions of the mammographic equipment. The indexes are calculated from a scoring system based on a designed algorithm which analyses the phantom image by means of an automatic detection of the test objects in each phantom.

Automated analysis of phantom images for the evaluation of long-term reproducibility in digital mammography

The performance of an automatic software package was evaluated with phantom images acquired by a full-field digital mammography unit. After the validation, the software was used, together with a Leeds TORMAS test object, to model the image acquisition process. Process modelling results were used to evaluate the sensitivity of the method in detecting changes of exposure parameters from routine image quality measurements in digital mammography, which is the ultimate purpose of long-term reproducibility tests. Image quality indices measured by the software included the mean pixel value and standard deviation of circular details and surrounding background, contrast-to-noise ratio and relative contrast; detail counts were also collected. The validation procedure demonstrated that the software localizes the phantom details correctly and the difference between automatic and manual measurements was within few grey levels. Quantitative analysis showed sufficient sensitivity to relate fluctuations in exposure parameters (kV(p) or mAs) to variations in image quality indices. In comparison, detail counts were found less sensitive in detecting image quality changes, even when limitations due to observer subjectivity were overcome by automatic analysis. In conclusion, long-term reproducibility tests provided by the Leeds TORMAS phantom with quantitative analysis of multiple IQ indices have been demonstrated to be effective in predicting causes of deviation from standard operating conditions and can be used to monitor stability in full-field digital mammography.

Monte Carlo image reconstruction of a mammographic phantom

The aim of this study is the development of a methodology to reconstruct via Monte Carlo techniques the radiographic image of the CIRS 11 A (MAMMO PHANTOM SP01) phantom. This phantom is used in image quality assessment during quality control tests in breast screening locations and other health centers. The mammographic phantom is comprised of a reference point, a glandular tissue step wedge, contrast and resolution targets, and groups of microcalcifications and fibers. The MCNP radiation transport code (version 4c2) has been modified and recompiled to let use of a large number of tallies and detectors per input file, and an azimuthal directional source biasing. The output surface air kerma (OSAK) delivered by the X-rays has been scored employing a rectangular matrix of point detectors (F5 tally) under the phantom, simulating the image system. Some variance reduction techniques have been implemented to ensure that photons reach the detectors and that weight fluctuations were reduced. The characteristic curve of the film-scanner imaging system combination has been obtained throughout several experimental measures with an aluminium sensitometric wedge and Monte Carlo simulations. The reconstructed images agree with the range of values, indicating that this method would be suitable for training purposes, phantom designing or dose calculations.

A comparative study of computer assisted assessment of image quality index for mammographic phantom images

Mammographic phantom images are usually used to study the quality of images obtained by dedicated mammographic equipment. The digital image treatment techniques allow us to carry out an automatic analysis of the phantom image. In this work, some techniques of digital image processing are applied to compute a specific image quality index (IQI) for a mammographic phantom, namely CIRS model 11A version SP01. The algorithm designed analyses the phantom image by means of automatic detection of the number of microcalcifications, and the image resolution as the number of line pairs per millimetre. Then, the IQI is calculated from a scoring system. The manner in which the functioning conditions (kV and mAs) of the mammographic equipment and the preprocessing denoising method of the digital image affect the results for the IQI are also studied.