scholarly journals Spectral CT of the extremities with a silicon strip photon counting detector

2015 ◽  
Author(s):  
A. Sisniega ◽  
W. Zbijewski ◽  
J. W. Stayman ◽  
J. Xu ◽  
K. Taguchi ◽  
...  
Keyword(s):  
Photon Counting ◽  
Spectral Ct ◽  
Photon Counting Detector

scholarly journals Material Discrimination Based on K-edge Characteristics

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Peng He ◽  
Biao Wei ◽  
Peng Feng ◽  
Mianyi Chen ◽  
Deling Mi
Keyword(s):  
Photon Counting ◽  
Reconstructed Image ◽  
Optimization Approach ◽  
Spectral Ct ◽  
Target Region ◽  
Photon Counting Detector ◽  
Available Energy ◽  
Imaging Model ◽  
Material Discrimination ◽  
Attenuation Profile

Spectral/multienergy CT employing the state-of-the-art energy-discriminative photon-counting detector can identify absorption features in the multiple ranges of photon energies and has the potential to distinguish different materials based on K-edge characteristics. K-edge characteristics involve the sudden attenuation increase in the attenuation profile of a relatively high atomic number material. Hence, spectral CT can utilize material K-edge characteristics (sudden attenuation increase) to capture images in available energy bins (levels/windows) to distinguish different material components. In this paper, we propose an imaging model based on K-edge characteristics for maximum material discrimination with spectral CT. The wider the energy bin width is, the lower the noise level is, but the poorer the reconstructed image contrast is. Here, we introduce the contrast-to-noise ratio (CNR) criterion to optimize the energy bin width after the K-edge jump for the maximum CNR. In the simulation, we analyze the reconstructed image quality in different energy bins and demonstrate that our proposed optimization approach can maximize CNR between target region and background region in reconstructed image.

scholarly journals Spectral CT reconstruction with an explicit photon-counting detector model: a one-step approach

2018 ◽  
Author(s):  
Pierre-Antoine Rodesch ◽  
Véronique Rebuffel ◽  
Clarisse Fournier ◽  
Florence Forbes ◽  
L. Verger
Keyword(s):  
Photon Counting ◽  
Ct Reconstruction ◽  
Spectral Ct ◽  
Photon Counting Detector ◽  
One Step ◽  
Detector Model

Combination of current-integrating/photon-counting detector modules for spectral CT

2013 ◽  
Vol 58 (19) ◽  
pp. 7009-7024 ◽  
Author(s):  
Jiyang Chu ◽  
Wenxiang Cong ◽  
Liang Li ◽  
Ge Wang
Keyword(s):  
Photon Counting ◽  
Spectral Ct ◽  
Photon Counting Detector

scholarly journals Quantitative dual contrast photon-counting computed tomography for assessment of articular cartilage health

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Petri Paakkari ◽  
Satu I. Inkinen ◽  
Miitu K. M. Honkanen ◽  
Mithilesh Prakash ◽  
Rubina Shaikh ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Articular Cartilage ◽  
Contrast Agent ◽  
Contrast Agents ◽  
Photon Counting ◽  
Spectral Imaging ◽  
Ct Scanning ◽  
Photon Counting Detector ◽  
Tissue Contrast ◽  
Reference Parameters

AbstractPhoton-counting detector computed tomography (PCD-CT) is a modern spectral imaging technique utilizing photon-counting detectors (PCDs). PCDs detect individual photons and classify them into fixed energy bins, thus enabling energy selective imaging, contrary to energy integrating detectors that detects and sums the total energy from all photons during acquisition. The structure and composition of the articular cartilage cannot be detected with native CT imaging but can be assessed using contrast-enhancement. Spectral imaging allows simultaneous decomposition of multiple contrast agents, which can be used to target and highlight discrete cartilage properties. Here we report, for the first time, the use of PCD-CT to quantify a cationic iodinated CA4+ (targeting proteoglycans) and a non-ionic gadolinium-based gadoteridol (reflecting water content) contrast agents inside human osteochondral tissue (n = 53). We performed PCD-CT scanning at diffusion equilibrium and compared the results against reference data of biomechanical and optical density measurements, and Mankin scoring. PCD-CT enables simultaneous quantification of the two contrast agent concentrations inside cartilage and the results correlate with the structural and functional reference parameters. With improved soft tissue contrast and assessment of proteoglycan and water contents, PCD-CT with the dual contrast agent method is of potential use for the detection and monitoring of osteoarthritis.

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