Abstract
Propagation-based X-ray phase-contrast imaging (PBI) is a powerful nondestructive imaging technique that can reveal the internal detailed structures in weakly absorbing samples. Extending PBI to CT (PBCT) enables high-resolution and high-contrast 3D visualization of microvasculature, which can be used for the understanding, diagnosis and therapy of diseases involving vasculopathy, such as cardiovascular disease, stroke and tumor. However, the long scan time for PBCT impedes its wider use in biomedical and preclinical microvascular studies. To address this issue, a novel CT reconstruction algorithm for PBCT is presented that aims at shortening the scan time for microvascular samples by reducing the number of projections while maintaining the high quality of reconstructed images. The proposed algorithm combines the filtered backprojection method into the iterative reconstruction framework, and a weighted guided image filtering approach (WGIF) is utilized to optimize the intermediate reconstructed images. Notably, the homogeneity assumption on the microvasculature sample is adopted as prior knowledge, and therefore, a prior image of microvasculature structures can be acquired by a k-means clustering approach. Then, the prior image is used as the guided image in the WGIF procedure to effectively suppress streaking artifacts and preserve microvasculature structures. To evaluate the effectiveness and capability of the proposed algorithm, simulation experiments on 3D microvasculature numerical phantom and real experiments with CT reconstruction on the microvasculature sample are performed. The results demonstrate that the proposed algorithm can, under noise-free and noisy conditions, significantly reduce the artifacts and effectively preserve the microvasculature structures on the reconstructed images and thus enables it to be used for clear and accurate 3D visualization of microvasculature from few-projection data. Therefore, for 3D visualization of microvasculature, the proposed algorithm can be considered an effective approach for reducing the scan time required by PBCT.
Highlights
Microvasculature usually refers to the network of small blood vessels with less than 100 μm diameter, including capillaries, venules and arterioles
As the number of projections decreased, the profiles of the reconstructed images using the proposed algorithm remained smooth in the homogeneous areas and near the boundaries (see Fig. 3(d, h, l)), which demonstrates that the proposed algorithm has the ability to suppress the streaking artifacts in the homogeneous areas and preserve the boundaries
As the widely used filtered backprojection (FBP) algorithm fails to reconstruct high-quality synchrotron radiation (SR)-PBI to CT (PBCT) images of microvasculature under the few-projection conditions, we developed a new few-projection SRPBCT reconstruction algorithm for microvasculature imaging
Summary
Microvasculature usually refers to the network of small blood vessels with less than 100 μm diameter, including capillaries, venules and arterioles. The development and variation in many diseases are associated with alterations of microvascular structure and morphology (e.g., changes in vessel diameter, vascular distortion and vascular network complexity), such as cardiovascular disease, stroke and tumor. The preparation of histopathological material requires tissue dissection, formalin fixation, paraffin embedding, tissue slicing and staining. This procedure may cause the deformation of anatomy and limit further analysis with different methods [4]. Analyzing the 3D characteristics of microvasculature architecture and morphology is important because it allows one to evaluate, at the micrometer scale, the relationship between structure and function for advancing the understanding of the role of vasculature that cannot be fully analyzed in 2D representative sections. A nondestructive imaging technique as a possible adjunct to histopathology, which allows 3D visualization and quantification of complicated microvascular networks while retaining a precise anatomical context, is required
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