Sparse reconstruction from a limited projection number of the coronary artery tree in X-ray rotational imaging

International audienceThis paper deals with the 3D reconstruction of sparse data in X-ray rotational imaging. Due to the cardiac motion, the number of available projections for this reconstruction is equal to four, which leads to a strongly undersampled reconstruction problem. We address thus this illness problem through a regularized iterative method. The whole algorithm is divided into two steps. Firstly, a minimal path segmentation step extracts artery tree boundaries. Secondly, a MAP reconstruction comparing L0-norm and L1-norm priors is applied on this extracted coronary tree. The reconstruction optimization process relies on a separable paraboloidal (SPS) algorithm. Some preliminary results are provided on simulated rotational angiograms

DICOM for EIT

With EIT starting to be used in routine clinical practice [1], it important that the clinically relevant information is portable between hospital data management systems. DICOM formats are widely used clinically and cover many imaging modalities, though not specifically EIT. We describe how existing DICOM specifications, can be repurposed as an interim solution, and basis from which a consensus EIT DICOM ‘Supplement’ (an extension to the standard) can be writte

Estimation of thorax shape for forward modelling in lungs EIT

The thorax models for pre-term babies are developed based on the CT scans from new-borns and their effect on image reconstruction is evaluated in comparison with other available models

Rapid generation of subject-specific thorax forward models

For real-time monitoring of lung function using accurate patient geometry, shape information needs to be acquired and a forward model generated rapidly. This paper shows that warping a cylindrical model to an acquired shape results in meshes of acceptable mesh quality, in terms of stretch and aspect ratio

Torso shape detection to improve lung monitoring

Two methodologies are proposed to detect the patient-specific boundary of the chest, aiming to produce a more accurate forward model for EIT analysis. Thus, a passive resistive and an inertial prototypes were prepared to characterize and reconstruct the shape of multiple phantoms. Preliminary results show how the passive device generates a minimum scatter between the reconstructed image and the actual shap

Nanoparticle electrical impedance tomography

We have developed a new approach to imaging with electrical impedance tomography (EIT) using gold nanoparticles (AuNPs) to enhance impedance changes at targeted tissue sites. This is achieved using radio frequency (RF) to heat nanoparticles while applying EIT imaging. The initial results using 5-nm citrate coated AuNPs show that heating can enhance the impedance in a solution containing AuNPs due to the application of an RF field at 2.60 GHz

Research Status and Prospect for CT Imaging

Computed tomography (CT) is a very valuable imaging method and plays an important role in clinical diagnosis. As people pay more and more attention to radiation doses these years, decreasing CT radiation dose without affecting image quality is a hot direction for research of medical imaging in recent years. This chapter introduces the research status of low-dose technology from following aspects: low-dose scan implementation, reconstruction methods and image processing methods. Furthermore, other technologies related to the development tendency of CT, such as automatic tube current modulation technology, rapid peak kilovoltage (kVp) switching technology, dual-source CT technology and Nano-CT, are also summarized. Finally, the future research prospect are discussed and analyzed

Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography

We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine