1. |
- Bornefalk, Hans, et al.
(author)
-
Simulation study of an energy sensitive photon counting silicon strip detector for computed tomography : identifying strengths and weaknesses and developing work-arounds
- 2010
-
In: MEDICAL IMAGING 2010. - : SPIE. - 9780819480231
-
Conference paper (peer-reviewed)abstract
- We model the effect of signal pile-up on the energy resolution of a photon counting silicon detector designed for high flux spectral CT with sub-millimeter pixel size. Various design parameters, such as bias voltage, lower threshold level for discarding of electronic noise and the entire electronic read out chain are modeled and realistic parameter settings are determined. We explicitly model the currents induced on the collection electrodes of a pixel and superimpose signals emanating from events in neighboring pixels, either due to charge sharing or signals induced during charge collection. Electronic noise is added to the pulse train before feeding it through a model of the read out electronics where the pulse height spectrum is saved to yield the detector energy response function. The main result of this study is that a lower threshold of 5 keV and a rather long time constant of the shaping filter (tau(0) = 30 ns) are needed to discard induced pulses from events in neighboring pixels. These induction currents occur even if no charge is being deposited in the analyzed pixel from the event in the neighboring pixel. There is also only a limited gain in energy resolution by increasing the bias voltage to 1000 V from 600 V. We show that with these settings the resulting energy resolution, as measured by the FWHM/E of the photo peak, is 5% at 70 keV.
|
|
2. |
- Fredenberg, Erik, PhD, 1979-, et al.
(author)
-
Observer model optimization of a spectral mammography system
- 2010
-
In: Medical Imaging 2010. - : SPIE. - 9780819480231
-
Conference paper (peer-reviewed)abstract
- 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. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, 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. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.
|
|