Mounting evidence suggests that the superposition of anatomical clutter in x-ray chest radiography poses a major impediment to the detectability of subtle lung nodules. Through decomposition of projections acquired using different x-ray energy spectra, dual-energy (DE) imaging offers to dramatically improve lung nodule conspicuity. The development of a high-performance DE chest imaging system is reported, with design and implementation guided by fundamental imaging performance metrics. Analytical and experimental studies of imaging performance guided the optimization of key acquisition technique parameters, including x-ray filtration, allocation of dose between low- and high-energy projections, and peak-kilovoltage selection. To minimize anatomical misregistration between images, a cardiac gating system was designed and implemented to direct x-ray exposures to within the quiescent period of the heart cycle. The instrumentation and optimal imaging techniques have been incorporated in a DE imaging prototype system now deployed in a clinical study to evaluate the diagnostic performance of DE imaging.

Mounting evidence suggests that the superposition of anatomical clutter in x-ray chest radiography poses a major impediment to the detectability of subtle lung nodules. Through decomposition of projections acquired using different x-ray energy spectra, dual-energy (DE) imaging offers to dramatically improve lung nodule conspicuity. The development of a high-performance DE chest imaging system is reported, with design and implementation guided by fundamental imaging performance metrics. Analytical and experimental studies of imaging performance guided the optimization of key acquisition technique parameters, including x-ray filtration, allocation of dose between low- and high-energy projections, and peak-kilovoltage selection. To minimize anatomical misregistration between images, a cardiac gating system was designed and implemented to direct x-ray exposures to within the quiescent period of the heart cycle. The instrumentation and optimal imaging techniques have been incorporated in a DE imaging prototype system now deployed in a clinical study to evaluate the diagnostic performance of DE imaging.

This thesis presents techniques constructed to aid the radiologists in detecting breast cancer, the second largest cause of cancer deaths for western women. In the first part of the thesis, a computer-aided detection (CAD) system constructed for the detection of stellate lesions is presented. Different segmentation methods and an attempt to incorporate contra-lateral information are evaluated. In the second part, a new method for evaluating such CAD systems is presented based on constructing credible regions for the number of false positive marks per image at a certain desired target sensitivity. This method shows that the resulting regions are rather wide and this explains some of the difficulties encountered by other researchers when trying to compare CAD algorithms on different data sets. In this part an attempt to model the clinical use of CAD as a second look is also made and it shows that applying CAD in sequence to the radiologist in a routine manner, without duly altering the decision criterion of the radiologist, might very well result in suboptimal operating points. Finally, in the third part two dual-energy imaging methods optimized for contrast-enhanced imaging of breast tumors are presented. The first is based on applying an electronic threshold to a photon-counting digital detector to discriminate between high- and low-energy photons. This allows simultaneous acquisition of the high- and low-energy images. The second method is based on the geometry of a scanned multi-slit system and also allows single-shot contrast-enhanced dual-energy mammography by filtering the x-ray beam that reaches different detector lines differently. / QC 20100819

Contrast-enhanced mammography (CEM) relies on visualizing the growth of new blood vessels (i.e. tumor angiogenesis) to provide sufficient materials for cell proliferation during the development of cancer. Since cancers will accumulate an injected contrast agent more than other tissues, it is possible to use one of several methods to enhance the area of lesions in the x-ray image and remove the contrast of normal tissue. Large area flat panel detectors may be used for CEM wherein the subtraction of two acquired images is used to create the resulting enhanced image. There exist several methods to acquire the images to be subtracted, which include temporal subtraction (pre- and post-contrast images) and dual-energy subtraction (low- and high-energy images), however these methods suffer from artifacts due to patient motion between image acquisitions. In this research the use of a multilayer flat panel detector is examined for CEM that is designed to acquire both (low- and high-energy) images simultaneously, thus avoiding motion artifacts in the resulting subtracted image. For comparison, a dual-energy technique prone to motion artifacts that uses a single-layer detector is also investigated. Both detectors are evaluated and optimized using amorphous selenium as the x-ray to charge conversion material, however the theoretical analysis could be extended to other conversion materials. Experimental results of single pixel prototypes of both multilayer and single-layer detectors are also discussed and compared to theoretical results. For a more comprehensive analysis, the motion artifacts present in dual-exposure techniques are modeled and the performance degradation due to motion artifacts is estimated. The effects of noise reduction techniques are also evaluated to determine potential image quality improvements in CEM images.

Contrast-enhanced mammography (CEM) relies on visualizing the growth of new blood vessels (i.e. tumor angiogenesis) to provide sufficient materials for cell proliferation during the development of cancer. Since cancers will accumulate an injected contrast agent more than other tissues, it is possible to use one of several methods to enhance the area of lesions in the x-ray image and remove the contrast of normal tissue. Large area flat panel detectors may be used for CEM wherein the subtraction of two acquired images is used to create the resulting enhanced image. There exist several methods to acquire the images to be subtracted, which include temporal subtraction (pre- and post-contrast images) and dual-energy subtraction (low- and high-energy images), however these methods suffer from artifacts due to patient motion between image acquisitions. In this research the use of a multilayer flat panel detector is examined for CEM that is designed to acquire both (low- and high-energy) images simultaneously, thus avoiding motion artifacts in the resulting subtracted image. For comparison, a dual-energy technique prone to motion artifacts that uses a single-layer detector is also investigated. Both detectors are evaluated and optimized using amorphous selenium as the x-ray to charge conversion material, however the theoretical analysis could be extended to other conversion materials. Experimental results of single pixel prototypes of both multilayer and single-layer detectors are also discussed and compared to theoretical results. For a more comprehensive analysis, the motion artifacts present in dual-exposure techniques are modeled and the performance degradation due to motion artifacts is estimated. The effects of noise reduction techniques are also evaluated to determine potential image quality improvements in CEM images.