An investigation of the imaging performance of CCD based x-ray detectors for digital mammography

This thesis describes the imaging performance of a prototype digital mammography system based upon charge coupled devices (CCDs). The imaging performance of these detectors is dependent upon the configuration of the detector. In this thesis the performance of 14 different detector configurations are studied for use in digital mammography. Experimental evaluations of factors which affect the performance of imaging systems such as quantum detection efficiency, dynamic range, modulation transfer function (MTF(f)) and Noise power spectrum (NPS) were performed. The use of spatial frequency dependent detective quantum efficiency DQE(f) to characterise the detectors in terms of signal to noise ratio transfer is described. It is shown that direct interactions of x-rays in the CCD act to reduce DQE(f) at high spatial frequencies and severely impair the detectors ability to detect small objects (250|im in diameter). The use of a sufficient thickness of fibre optic faceplate to couple the phosphor layer to the CCD is shown to remove these interactions and shows a corresponding increase in DQE(f) (at higher spatial frequencies) and the detector's ability to image smaller objects A subjective comparison of images of a breast phantom shows that images of superior quality were obtained with the prototype system compared with images produced using a conventional film-screen system, for a slight increase in dose. Improvements to the system and detector design are presented and will act to try to produce the same image quality for equivalent doses used in conventional mammography

An investigation into the use of charge-coupled devices for digital mammography

This thesis describes the design, optimisation, construction and evaluation of a laboratory based digital mammography system which uses phosphor coated charge-coupled devices (CCDs) for x-ray detection. The size mismatch between the breast and the CCD is overcome by operating the CCD in time delay and integration (TDI) mode and scanning across the breast. Multiparameter optimisations have been carried out for a wide range of digital mammography system configurations and requirements, with the aim of optimising the image quality for a given patient dose. The influence of slot width, exposure time, focal spot size, detector resolution and noise level, dose restrictions, patient thickness and x- ray tube target on the system configuration to give optimum image quality is examined. The system is fully characterised in terms of responsivity, dark current, modulation transfer functions (MTFs), noise power spectra (NPS) and spatial frequency dependent detective quantum efficiency (DQE(f)). Direct interactions of x-rays with the CCD are shown to give a significant increase in the high frequency values of the MTF. These interactions also act as a source of noise and act to significantly reduce the DQE(f) at all frequencies. A subjective comparison of images produced with the optimised prototype system with those produced using a conventional film-screen detector shows that these interactions must be removed if the prototype system is to produce images of equal quality to those currently produced using film-screen combinations. Other improvements to the system are suggested

Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging

Recently CMOS Active Pixels Sensors (APSs) have become a valuable alternative to amorphous Silicon and Selenium Flat Panel Imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ≤ 1.9%. The uniformity of the image quality performance has been further investigated in a typical X-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practise. Finally, in order to compare the detection capability of this novel APS with the currently used technology (i.e. FPIs), theoretical evaluation of the Detection Quantum Efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, X-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications

Apodized-Aperture Pixel Design X-Ray Detector for Improvement of Detective Quantum Efficiency at High Spatial Frequencies

The detective quantum efficiency (DQE) is a characteristic of x-ray imaging systems describing how well a system can produce high signal-to-noise ratio images compared to an ideal detector. In medical radiography, increases in DQE result directly in increases in image SNR for a given x-ray exposure, and improved SNR has been shown to improve breast cancer detection rates in screening programs. Typically, modern x-ray detectors have DQE values about 0.6 to 0.7 at low spatial frequencies and 0.2 to 0.3 or less at high spatial frequencies. We describe a method to improve the high frequency DQE by developing a novel apodized-aperture pixel (AAP) design that can be implemented with detectors having very small elements. We show theoretically that the high-frequency DQE can be doubled using this approach. Experimental validation shows an increase from 0.2 to 0.4 at the sampling cut-off frequency (2.5 cycles/mm) for a laboratory CMOS/CsI detector. It is predicted the high-frequency DQE of a Se-based detector for mammography could be increased from 0.35 to 0.7. Such increases would improve visualization of small objects and fine detail in x-ray imaging by a factor of two

Digital radiography: image acquisition and scattering reduction in x-ray imaging.

Since the discovery of the X-rays in 1895, their use in both medical and industrial imaging applications has gained increasing importance. As a consequence, X-ray imaging devices have evolved and adapted to the needs of individual applications, leading to the appearance of digital image capture devices. Digital technologies introduced the possibility of separating the image acquisition and image processing steps, allowing their individual optimization. This thesis explores both areas, by seeking the improvement in the design of the new family of Varex Imaging CMOS X-ray detectors and by developing a method to reduce the scatter contribution in mammography examinations using image post-processing techniques. During the CMOS X-ray detector product design phase, it is crucial to detect any short- comings that the detector might present. Image characterization techniques are a very efficient method for finding these possible detector features. This first part of the thesis focused in taking these well-known test methods and adapt and optimize them, so they could act as a red flag indicating when something needed to be investigated. The methods chosen in this study have proven to be very effective in finding detector short- comings and the designs have been optimised in accordance with the results obtained. With the aid of the developed imaging characterization tests, new sensor designs have been successfully integrated into a detector, resulting in the recent release into the market of a new family of Varex Imaging CMOS X-ray detectors. The second part of the thesis focuses in X-ray mammography applications, the gold standard technique in breast cancer screening programmes. Scattered radiation degrades the quality of the image and complicates the diagnosis process. Anti-scatter grids, the main scattering reduction technique, are not a perfect solution. This study is concerned with the use of image post-processing to reduce the scatter contribution in the image, by convolving the output image with kernels obtained from simplified Monte Carlo simulations. The proposed semi-empirical approach uses three thickness-dependant symmetric kernels to accurately estimate the environment contribution to the breast, which has been found to be of key importance in the correction of the breast-edge area. When using a single breast thickness-dependant kernel to convolve the image, the post-processing technique can over-estimate the scattering up to 60%. The method presented in this study reduces the uncertainty to a 4-10% range for a 35 to 70 mm breast thickness range, making it a very efficient scatter modelling technique. The method has been successfully proven against full Monte Carlo simulations and mammography phantoms, where it shows clear improvements in terms of the contrast to noise ratio and variance ratio when the performance is compared against images acquired with anti-scatter grids

The Dexela 2923 CMOS X-ray detector: A flat panel detector based on CMOS active pixel sensors for medical imaging applications

Complementary metal-oxide-semiconductors (CMOS) active pixel sensors (APS) have been introduced recently in many scientific applications. This work reports on the performance (in terms of signal and noise transfer) of an X-ray detector that uses a novel CMOS APS which was developed for medical X-ray imaging applications. For a full evaluation of the detector's performance, electro-optical and X-ray characterizations were carried out. The former included measuring read noise, full well capacity and dynamic range. The latter, which included measuring X-ray sensitivity, presampling modulation transfer function (pMTF), noise power spectrum (NPS) and the resulting detective quantum efficiency (DQE), was assessed under three beam qualities (28 kV, 50 kV (RQA3) and 70 kV (RQA5) using W/Al) all in accordance with the IEC standard. The detector features an in-pixel option for switching the full well capacity between two distinct modes, high full well (HFW) and low full well (LFW). Two structured CsI:Tl scintillators of different thickness (a “thin” one for high resolution and a thicker one for high light efficiency) were optically coupled to the sensor array to optimize the performance of the system for different medical applications. The electro-optical performance evaluation of the sensor results in relatively high read noise (∼360 e−), high full well capacity (∼1.5×106 e−) and wide dynamic range (∼73 dB) under HFW mode operation. When the LFW mode is used, the read noise is lower (∼165) at the expense of a reduced full well capacity (∼0.5×106 e−) and dynamic range (∼69 dB). The maximum DQE values at low frequencies (i.e. 0.5 lp/mm) are high for both HFW (0.69 for 28 kV, 0.71 for 50 kV and 0.75 for 70 kV) and LFW (0.69 for 28 kV and 0.7 for 50 kV) modes. The X-ray performance of the studied detector compares well to that of other mammography and general radiography systems, obtained under similar experimental conditions. This demonstrates the suitability of the detector for both mammography and general radiography, with the use of appropriate scintillators. The high DQE values obtained under low mammographic exposures (up to 0.65 for 22.3 μGy) matches the demand for high detectability in imaging of the dense breast

Feature analysis methods for intelligent breast imaging parameter optimisation using CMOS active pixel sensors

This thesis explores the concept of real time imaging parameter optimisation in digital mammography using statistical information extracted from the breast during a scan. Transmission and Energy dispersive x-ray diffraction (EDXRD) imaging were the two very different imaging modalities investigated. An attempt to determine if either could be used in a real time imaging system enabling differentiation between healthy and suspicious tissue regions was made. This would consequently enable local regions (potentially cancerous regions) within the breast to be imaged using optimised imaging parameters. The performance of possible statistical feature functions that could be used as information extraction tools were investigated using low exposure breast tissue images. The images were divided into eight regions of interest, seven regions corresponding to suspicious tissue regions marked by a radiologist, where the final region was obtained from a location in the breast consisting solely of healthy tissue. Results obtained from this investigation showed that a minimum of 82% of the suspicious tissue regions were highlighted in all images, whilst the total exposure incident on the sample was reduced in all instances. Three out of the seven (42%) intelligent images resulted in an increased contrast to noise ratio (CNR) compared to the conventionally produced transmission images. Three intelligent images were of similar diagnostic quality to their conventional counter parts whilst one was considerably lower. EDXRD measurements were made on breast tissue samples containing potentially cancerous tissue regions. As the technique is known to be able to distinguish between breast tissue types, diffraction signals were used to produce images corresponding to three suspicious tissue regions consequently enabling pixel intensities within the images to be analysed. A minimum of approximately 70% of the suspicious tissue regions were highlighted in each image, with at least 50% of each image remaining unsuspicious, hence was imaged with a reduced incident exposure