Model-based inter- and intra-panel inconsistency correction for photon counting detector CT

2021 ◽  
Author(s):  
Mang Feng ◽  
Xu Ji ◽  
Ran Zhang ◽  
Ke Li
Keyword(s):  
Photon Counting ◽  
Photon Counting Detector ◽  
Model Based

A photon counting detector model based on increment matrices to simulate statistically correct detector signals

2015 ◽  
Author(s):  
Sebastian Faby ◽  
Joscha Maier ◽  
David Simons ◽  
Heinz-Peter Schlemmer ◽  
Michael Lell ◽  
...  
Keyword(s):  
Photon Counting ◽  
Photon Counting Detector ◽  
Model Based ◽  
Detector Model

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.

scholarly journals A Universal Protocol for Abdominal CT Examinations Performed on a Photon-Counting Detector CT System

2020 ◽  
Vol 55 (4) ◽  
pp. 226-232
Author(s):  
Wei Zhou ◽  
Gregory J. Michalak ◽  
Jayse M. Weaver ◽  
Hao Gong ◽  
Lifeng Yu ◽  
...  
Keyword(s):  
Photon Counting ◽  
Abdominal Ct ◽  
Photon Counting Detector ◽  
Ct System ◽  
Universal Protocol

scholarly journals Detection of Microcalcifications in Spiral Breast Computed Tomography with Photon-Counting Detector Is Feasible: A Specimen Study

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 848
Author(s):  
Matthias Wetzl ◽  
Evelyn Wenkel ◽  
Eva Balbach ◽  
Ebba Dethlefsen ◽  
Arndt Hartmann ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Sensitivity And Specificity ◽  
Breast Biopsy ◽  
Photon Counting ◽  
Diagnostic Confidence ◽  
Voxel Size ◽  
Photon Counting Detector ◽  
Smooth Kernel ◽  
Higher Sensitivity ◽  
Breast Computed Tomography

The primary objective of the study was to compare a spiral breast computed tomography system (SBCT) to digital breast tomosynthesis (DBT) for the detection of microcalcifications (MCs) in breast specimens. The secondary objective was to compare various reconstruction modes in SBCT. In total, 54 breast biopsy specimens were examined with mammography as a standard reference, with DBT, and with a dedicated SBCT containing a photon-counting detector. Three different reconstruction modes were applied for SBCT datasets (Recon1 = voxel size (0.15 mm)3, smooth kernel; Recon2 = voxel size (0.05 mm)3, smooth kernel; Recon3 = voxel size (0.05 mm)3, sharp kernel). Sensitivity and specificity of DBT and SBCT for the detection of suspicious MCs were analyzed, and the McNemar test was used for comparisons. Diagnostic confidence of the two readers (Likert Scale 1 = not confident; 5 = completely confident) was analyzed with ANOVA. Regarding detection of MCs, reader 1 had a higher sensitivity for DBT (94.3%) and Recon2 (94.9%) compared to Recon1 (88.5%; p < 0.05), while sensitivity for Recon3 was 92.4%. Respectively, reader 2 had a higher sensitivity for DBT (93.0%), Recon2 (92.4%), and Recon3 (93.0%) compared to Recon1 (86.0%; p < 0.05). Specificities ranged from 84.7–94.9% for both readers (p > 0.05). The diagnostic confidence of reader 1 was better with SBCT than with DBT (DBT 4.48 ± 0.88, Recon1 4.77 ± 0.66, Recon2 4.89 ± 0.44, and Recon3 4.75 ± 0.72; DBT vs. Recon1/2/3: p < 0.05), while reader 2 found no differences. Sensitivity and specificity for the detection of MCs in breast specimens is equal for DBT and SBCT when a small voxel size of (0.05 mm)3 is used with an equal or better diagnostic confidence for SBCT compared to DBT.

Evaluation of Timepix3 based CdTe photon counting detector for fully spectroscopic small animal SPECT imaging

2018 ◽  
Vol 13 (01) ◽  
pp. C01001-C01001 ◽  
Author(s):  
E. Trojanova ◽  
J. Jakubek ◽  
D. Turecek ◽  
V. Sykora ◽  
P. Francova ◽  
...  
Keyword(s):  
Photon Counting ◽  
Small Animal ◽  
Spect Imaging ◽  
Photon Counting Detector
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