The field of X-ray imaging is currently undergoing a revolution due to the development of X-ray phase-contrast (PC) imaging methods that have dramatic advantages over conventional radiographic X-ray imaging systems. Conventional X-ray imaging methods are based on absorption effects and therefore image contrast is due to differences only in the X-ray absorption properties of the tissues. This can be problematic when imaging soft tissues that do not possess large variations in X-ray absorption properties. There remains an important need for optimization, improvement, characterization, and validation of PC imaging methods, to make them suitable for routine and widespread use. Our research group is actively developing image formation methods for X-ray PC imaging and is collaborating with several groups based at the Washington University in St. Louis School of Medicine and other institutions to translate the technology to address important needs in clinical and preclinical medicine.
Ongoing projects in our lab include the following:
Lung speckle imaging in propagation-based X-ray phase contrast imaging
Propagation-based X-ray Phase Contrast (PB-XPC) images of lungs reveal a speckled intensity distribution present only in lung regions. The speckle can be explained as multiple refractions at the numerous air-tissue interfaces the X-rays encounter as they travel through the lung. Information regarding airway microstructure that is encoded within speckle texture of a single XPC radiograph can be decoded to spatially resolve changes in lung properties such as microstructure sizes, air volumes, and compliance. Such functional information cannot be derived from conventional lung radiography or any other 2D imaging modality. By computing these images at different time points within a breathing cycle, dynamic functional imaging can be potentially achieved without the need for tomography. Previously only observed in synchrotron studies, we have demonstrated the first small animal XPC lung speckle images acquired with a bench top system in vivo. This imaging technique is well-suited for a wide range of pre-clinical pulmonary studies which investigate lung function, disease progression, and efficacy of treatment options.
Development of a resolution-enhancing image reconstruction method for few-view diﬀerential phase-contrast tomography
An important application of diﬀerential X-ray phase-contrast tomography (D-XPCT) within the reach of currently available imaging hardware is high-resolution imaging of biomedical samples. However, reconstructing high resolution D-XPCT images from few-view tomographic measurements remains a challenging task that has not been systematically explored. We are now developing a non-conventional objective function used for few-view iterative D-XPCT image reconstruction. It can potentially mitigate the high-frequency information loss caused by data incompleteness and produce images that have better preserved high spatial frequency content than those produced by use of a conventional penalized least squares (PLS) estimator. The proposed algorithm is being investigated by use of experimental data produced by an edge-illumination XPCT imager.
The development of a constrained method for stabilized quantitative projection-based dual-energy material decomposition
Dual-energy imaging has demonstrated the ability to improve the diagnostic potential of x-ray images in many areas of clinical practice. Because image-based material decomposition is relatively easy and fast to implement, dual-energy computed tomography has made many advances during the last decade and is available in several commercialized imaging systems. However, there is still a lack of reliable and valid methods for projection-based material decomposition, which remains a bottleneck for the development of dual-energy computed radiography. One main diﬃculty existing for projection-based decomposition is the extreme sensitivity to data noise, as the ﬁtting functions are usually high-order polynomials. We demonstrate that a constraint of total projection length can signiﬁcantly stabilize the decomposition process. This constraint enables a fast convergence to a realistic solution of the least-square sum optimization problem, which proves to be very robust to the data noise. We have obtained results from numerical simulations demonstrating that the new method is able to compute basis material images with considerable accuracy in terms of the quantities of projected thicknesses of basis materials, which may prove use in the future clinical diagnosis.
The development of advanced iterative reconstruction algorithm for Tetrahedron beam computed tomography (TBCT) (Collaboration with Dr. Tiezhi Zhang)
Recently a novel tetrahedron beam computed tomography (TBCT) imaging system which consists of a linear scan x-ray source and a linear x-ray detector array has been proposed and developed. TBCT is similar to CBCT in image reconstruction geometry; however, its image quality will be significantly superior to that of CBCT due to its scatter rejection mechanism. We are developing an advanced iterative reconstruction algorithm specifically designed for TBCT, which enables the reduction of data acquisition and the improvement of the image quality. The algorithm also helps investigate the potential advantage in z-resolution preservation of TBCT modality compared with the conventional CBCT.
Development of an optimized data acquisition method for CBCT scatters reduction and image quality improvement (Collaboration with Dr. Hua Li)
X-ray scatter degrades the quality of cone-beam computed tomography (CBCT) and represents a problem in volumetric image guided and adaptive radiation therapy. We propose an optimized data acquisition method to achieve scatter reduction and improved reconstruction image quality. One method of reducing scattered radiation and increasing soft-tissue contrast is to shrink the ﬁeld size with X-ray beam collimators or other beam-limiting devices. However, this method is limited by the necessity to cover only a speciﬁc anatomical region of interest (ROI). Moreover, the truncated projections lose the view of the rest of body, and the severe truncation artifacts still remain a big problem for ROI reconstruction. We propose to acquire two sets of projection views: one set of low-contrast projections that normally include the whole body, and another set of high-contrast projections that only cover the ROI but contain fewer scattered photons. An advanced algorithm will combine these two types of data sets, preserving a whole-body reconstruction without information loss (truncation), and at the same time reducing the scatter level especially in the ROI where an enhanced soft-tissue contrast is expected. We will also address an acquisition optimization problem regarding the distribution of the truncated projections when the total number of acquired projections is given and limited.
Investigation of the depth resolution properties of propagation-based X-ray phase-contrast tomosynthesis
Propagation-based X-ray phase-contrast (PB-XPC) tomosynthesis combines the concepts of tomosynthesis and XPC imaging to utilize the advantages of both for clinical imaging applications (e.g. breast and lung tumor screen). While previous studies showed PB-XPC tomosynthesis is able to provide boundary-enhanced in-plane images with better conspicuity than conventional absorption-based (AB) tomosynthesis, there is still a lack of analyses and experiments that investigate the depth resolution properties along the third dimension in reconstructed volumes. As PB-XPC tomosynthesis data function contains large magnitudes of high frequency components coming from the Fresnel diffraction patterns, we noticed the Fourier slice theorem implies the ability of XPC tomosynthesis to present improved detectability of ﬁne spatial features in spite of limited scanning angle range. We are proposing numerical and experimental investigations to compare the potential of AB tomosynthesis and PB-XPC tomosynthesis techniques for distinguishing depth positions of features in reconstructed images. Preliminary results show that, for PB-XPC tomosynthesis, in-plane structures display strong phase-contrast-induced fringes, while out-of-plane structures usually do not. This effect can facilitate the discrimination of in-plane structures, thus providing better depth position characterization than AB tomosynthesis.
Joint reconstruction of X-ray phase contrast computed tomography
X-ray phase-contrast computed tomography (XPCT) differs from conventional X-ray computed tomography since it reveals the refractive index distribution of the to-be-imaged object besides the absorption distribution. XPCT is especially good at imaging soft tissues whose absorption has low contrast. Conventional reconstruction algorithms generally consist of two steps: phase retrieval so that sinogram is generated for both absorption and refractive index, followed by conventional inverse Radon transformation algorithm such as filtered back projection (FBP). The phase retrieval step usually requires acquisition of multiple images from the same tomographic view angle, and thus increases data acquisition time and radiation dose. Our projects focus on developing joint reconstruction algorithms which allows single-shot imaging. As a result, it is possible to simplify XPCT systems, reduce data acquisition time and reduce radiation dose.