Contrast cancellation technique applied to digital x-ray imaging using silicon strip detectors

A novel approach to background subtraction in contrast-enhanced dual-energy digital mammography with commercially available mammography devices: Polychromaticity correction

PURPOSE

Contrast-enhanced digital mammography is an image subtraction technique that is able to improve the detectability of lesions in dense breasts. One of the main sources of error, when the technique is performed by means of commercial mammography devices, is represented by the intrinsic polychromaticity of the x-ray beams. The aim of the work is to propose an iterative procedure, which only assumes the knowledge of a small set of universal quantities, to take into account the polychromaticity and correct the subtraction results accordingly.

METHODS

In order to verify the procedure, it has been applied to an analytical simulation of a target containing a contrast medium and to actual radiographs of a breast phantom containing cavities filled with a solution of the same medium.

RESULTS

The reconstructed densities of contrast medium were compared, showing very good agreement between the theoretical predictions and the experimental results already after the first iteration. Furthermore, the convergence of the iterative procedure was studied, showing that only a small number of iterations is necessary to reach limiting values.

CONCLUSIONS

The proposed procedure represents an efficient solution to the polychromaticity issue, qualifying therefore as a viable alternative to inverse-map functions.

Tissue Cancellation in Dual Energy Mammography Using a Calibration Phantom Customized for Direct Mapping

An easily implementable tissue cancellation method for dual energy mammography is proposed to reduce anatomical noise and enhance lesion visibility. For dual energy calibration, the images of an imaging object are directly mapped onto the images of a customized calibration phantom. Each pixel pair of the low and high energy images of the imaging object was compared to pixel pairs of the low and high energy images of the calibration phantom. The correspondence was measured by absolute difference between the pixel values of imaged object and those of the calibration phantom. Then the closest pixel pair of the calibration phantom images is marked and selected. After the calibration using direct mapping, the regions with lesion yielded different thickness from the background tissues. Taking advantage of the different thickness, the visibility of cancerous lesions was enhanced with increased contrast-to-noise ratio, depending on the size of lesion and breast thickness. However, some tissues near the edge of imaged object still remained after tissue cancellation. These remaining residuals seem to occur due to the heel effect, scattering, nonparallel X-ray beam geometry and Poisson distribution of photons. To improve its performance further, scattering and the heel effect should be compensated.

Contrast-enhanced spectral mammography with a photon-counting detector

PURPOSE

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. The authors have investigated a photon-counting spectral imaging system with two energy bins for contrast-enhanced mammography. System optimization and the potential benefit compared to conventional non-energy-resolved absorption imaging was studied.

METHODS

A framework for system characterization was set up that included quantum and anatomical noise and a theoretical model of the system was benchmarked to phantom measurements.

RESULTS

Optimal combination of the energy-resolved images corresponded approximately to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging in the phantom study. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, yielded only a minute improvement. In a simulation of a clinically more realistic case, spectral imaging was predicted to perform approximately 30% better than absorption imaging for an average glandularity breast with an average level of anatomical noise. For dense breast tissue and a high level of anatomical noise, however, a rise in detectability by a factor of 6 was predicted. Another approximately 70%-90% improvement was found to be within reach for an optimized system.

CONCLUSIONS

Contrast-enhanced spectral mammography is feasible and beneficial with the current system, and there is room for additional improvements. Inclusion of anatomical noise is essential for optimizing spectral imaging systems.

Detectors for the future of X-ray imaging

In recent decades, developments in detectors for X-ray imaging have improved dose efficiency. This has been accomplished with for example, structured scintillators such as columnar CsI, or with direct detectors where the X rays are converted to electric charge carriers in a semiconductor. Scattered radiation remains a major noise source, and fairly inefficient anti-scatter grids are still a gold standard. Hence, any future development should include improved scatter rejection. In recent years, photon-counting detectors have generated significant interest by several companies as well as academic research groups. This method eliminates electronic noise, which is an advantage in low-dose applications. Moreover, energy-sensitive photon-counting detectors allow for further improvements by optimising the signal-to-quantum-noise ratio, anatomical background subtraction or quantitative analysis of object constituents. This paper reviews state-of-the-art photon-counting detectors, scatter control and their application in diagnostic X-ray medical imaging. In particular, spectral imaging with photon-counting detectors, pitfalls such as charge sharing and high rates and various proposals for mitigation are discussed.