Abstract
X-ray computed tomography (CT) is a powerful and routinely used clinical diagnostic technique, which is well tolerated by patients, and which provides high-resolution images and volumetric information about the body. However, two important limitations still affect this examination procedure: (1) its low sensitivity with respect to soft tissues, and (2) the hazards associated with x-ray exposure. Conventional radiology is based on the detection of the different photon absorption properties that characterize biological tissues, and thus the obtainable image contrast from soft and/or similar tissues is intrinsically limited. In this scenario, x-ray phase contrast imaging (XPCI) has been extensively tested and proven to overcome some of the main issues surrounding standard x-ray imaging. In addition to the absorption signal, XPCI relies on detecting the phase shifts induced by an object. Interestingly, as the order of magnitude of the phase contrast is higher than that of absorption, XPCI can, in principle, offer higher sensitivity at lower radiation doses. However, other technical aspects may counterbalance this gain, and an optimized setup and image processing solutions need to be implemented. The work presented here describes the strategies and developments we have realized, with the aim of controlling the radiation dose for the highly sensitive and quantitative XPCI-CT. Different algorithms for the phase retrieval and CT reconstruction of the XPCI data are presented. The CT algorithms we have implemented, namely the equally sloped tomography and the dictionary learning method, allow the image quality to be preserved while reducing the number of angular projections required by a factor of five. The results applied to breast imaging report accurate reconstructions at clinically compatible doses of the 3D distribution of the refractive properties of full human organs obtained by using three different phase retrieval methods. The described methodologies and the presented results have been validated by a team of clinical radiologists and represent an important step in the exploitation of XPCI-CT for in vivo and possible clinical applications.
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