We recently proposed a method for retrieving absorption and phase properties of samples using a set of spectral x-ray measurements obtained in phase enhanced geometries. The spectral measurements can be obtained using state-of-the-art photon counting detectors (PCDs). These detectors permit the use of polychromatic sources and record accurate spectroscopic information in each pixel from a single X-ray exposure. In previous simulations and benchtop experiments we demonstrated that our method can be used to obtain quantitatively accurate absorption and phase properties of samples with effective atomic numbers (Z<sub>eff</sub>) that are close to soft tissue. This report expands on those findings to include heterogeneous samples to emulate complex composition in biological materials as well as samples with relatively high Z<sub>eff</sub>, such as bones and microcalcifications. Here we also demonstrate that excellent quantitative estimates of multiple object properties can be simultaneously obtained for these heterogeneous samples when spectral data is available. These multi-contrast estimates would allow differentiation of materials that would otherwise be indistinguishable using conventional, absorption contrast imaging. These preliminary results including phase retrieval of Aluminum rod also confirms that the slowly varying phase approximation used in PB-PCI transport of intensity models will not hinder their applicability for complex tissue imaging and small animal imaging.
Recently, we proposed a multi-step material decomposition method for spectral CT where the decomposition is solved in a series of steps each separating one new material from the original attenuation data. Until now, this method has only been tested using numerical simulations of multi-material digital phantoms. Here we present the initial results of the multistep method applied to experimental data acquired in our laboratory using a Medipix 3RX detector with a silicon senor. The decomposition of CT images of a 3-material phantom is demonstrated. The materials studied here are gadolinium (Gd), iodine (I) and acrylonitrile butadiene styrene (ABS) plastic. The results show qualitative and quantitative improvement in separation accuracy as the worst-case percent error in one selected slice is reduced by 51.7% when using our new method in comparison to a conventional single-step material decomposition.
When using a photon counting detector (PCD) for material decomposition problems, a major issue is the low-count rate per energy bin which may lead to high image-noise with compromised contrast and accuracy. We recently proposed a multi-step algorithmic method of material decomposition for spectral CT, where the problem is formulated as a series of simpler and dose efficient decompositions rather than solved simultaneously. While the method offers higher flexibility in the choice of energy bins for each material type, there are several aspects that should be optimized for effective utility of these methods. A simple domain of four materials: water, calcium, iodine and gold was explored for testing these. The results showed an improvement in accuracy with low-noise over the single-step method where the materials were decomposed simultaneously. This paper presents a comparison of contrast-to-noise ratio (CNR) and retrieval accuracy in both single-step and multi-step methods under varying acquisition and reconstruction parameters such as Wiener filter kernel size, pixel binning, signal size and energy bin overlap.
In x-ray breast images, anatomical variations have been characterized by slope of the noise power spectrum (NPS) that follows an inverse power-law relationship. Prior literature has reported that this slope (β) changes with imaging modality (DBT vs. mammography) and with different reconstruction algorithms and filters for the same breast structures. In this paper, we assessed the relative contributions of anatomic and quantum noise in the estimated magnitude of β. This is achieved via simulations with varying levels of quantum noise and examining contributions of noise filters. The calculations were performed on simulated DBT images from anthropomorphic software breast phantoms under varying acquisition and reconstruction/filter parameters. Our results indicate that variations in β cannot be solely considered as an indicator of reduced “anatomic noise” and hence potentially improved detectability in those images; presence of quantum noise and view aliasing artifacts in anatomical region always lowered the value of β.
Proc. SPIE. 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment
KEYWORDS: Breast, Statistical analysis, X-ray computed tomography, Tumor growth modeling, Imaging systems, Image processing, Medical imaging, Tomography, Digital imaging, Image display, Signal detection, Digital breast tomosynthesis, Breast imaging
Understanding factors that influence search and localization of signals in tomographic breast imaging can allow for the development of efficient system design and image displays. Several acquisition, reconstruction and display parameters are known to influence signal (mass or microcalcification) detection. In this abstract we examine variation in relevant image texture features with respect to digital breast tomosynthesis (DBT) acquisition parameters. We shall relate the impact of these changes in detection via correlations against results obtained from human observer localization ROC (LROC) studies. Our methods included calculation and analysis of these texture features at randomly sampled ROIs in select image sets.
Photon counting spectral detectors are being investigated to allow better discrimination of multiple materials by collecting spectral data for every detector pixel. The process of material decomposition or discrimination starts with an accurate estimation of energy dependent attenuation of the composite object. Photoelectric effect and Compton scattering are two important constituents of the attenuation. Compton scattering while results in a loss of primary photon, also results in an increase in photon counts in the lower ene<sup>1</sup>rgy bins via multiple orders of scatter. This contribution to each energy bin may change with material properties, thickness and x-ray energies. There has been little investigation into the effect of this increase in counts at lower energies due to presence of these Compton scattered photons using photon counting detectors. Our investigations show that it is important to account for this effect in spectral decomposition problems.
When using a photon counting detector for material decomposition problems, a major issue is the low-count rate per energy bin which may lead to high image-noise with compromised contrast and accuracy. A multi-step algorithmic method of material decomposition is proposed for spectral computed tomography (CT), where the problem is formulated as series of simpler and dose efficient decompositions rather than solved simultaneously. A simple domain of four materials; water, hydroxyapatite, iodine and gold was explored. The results showed an improvement in accuracy with low-noise over a similar method where the materials were decomposed simultaneously. In the multi-step approach, for the same acquired energy bin data, the problem is reformulated in each step with decreasing number of energy bins (resulting in a higher count levels per bin) and unknowns in each step. This offers flexibility in the choice of energy bins for each material type. Our results are very preliminary but show promise and potential to tackle challenging decomposition tasks. Complete work will include detailed analysis of this approach and experimental data with more complex mixtures.
X-ray phase contrast imaging has been investigated during the last two decades for potential benefits in soft tissue
imaging. Long imaging time, high radiation dose and general measurement complexity involving motion of x-ray
optical components have prevented the clinical translation of these methods. In all existing popular phase contrast
imaging methods, multiple measurements per projection angle involving motion of optical components are required to
achieve quantitatively accurate estimation of absorption, phase and differential phase. Recently we proposed an
algorithmic approach to use spectral detection data in a phase contrast imaging setup to obtain absorption, phase and
differential phase in a single-step. Our generic approach has been shown via simulations in all three types of phase
contrast imaging: propagation, coded aperture and grating interferometry. While other groups have used spectral
detector in phase contrast imaging setups, our proposed method is unique in outlining an approach to use this spectral
data to simplify phase contrast imaging. In this abstract we show the first experimental proof of our single-shot phase
retrieval using a Medipix3 photon counting detector in an edge illumination aperture (also referred to as coded aperture)
phase contrast set up as well as for a free space propagation setup. Our preliminary results validate our new transport
equation for edge illumination PCI and our spectral phase retrieval algorithm for both PCI methods being investigated.
Comparison with simulations also point to excellent performance of Medipix3 built-in charge sharing correction