scholarly journals A Prototype Spatial‐Spectral CT System for Material Decomposition with Energy‐Integrating Detector

2021 ◽  
Author(s):  
Matthew Tivnan ◽  
Wenying Wang ◽  
J. Webster Stayman
Keyword(s):  
Spectral Ct ◽  
Material Decomposition ◽  
Ct System

scholarly journals Detection of Bone Marrow Edema in Patients with Osteoid Osteoma Using Three-Material Decomposition with Dual-Layer Spectral CT

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 953
Author(s):  
Florian T. Gassert ◽  
Johannes Hammel ◽  
Felix C. Hofmann ◽  
Jan Neumann ◽  
Claudio E. von Schacky ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Osteoid Osteoma ◽  
Bone Marrow Edema ◽  
Volume Fraction ◽  
Imaging Findings ◽  
Spectral Ct ◽  
Material Decomposition ◽  
Negative Imaging ◽  
Interreader Agreement ◽  
Marrow Edema

The aim of this study is to assess whether perifocal bone marrow edema (BME) in patients with osteoid osteoma (OO) can be accurately detected on dual-layer spectral CT (DLCT) with three-material decomposition. To that end, 18 patients with OO (25.33 ± 12.44 years; 7 females) were pairwise-matched with 18 patients (26.72 ± 9.65 years; 9 females) admitted for suspected pathologies other than OO in the same anatomic location but negative imaging findings. All patients were examined with DLCT and MRI. DLCT data was decomposed into hydroxyapatite and water- and fat-equivalent volume fraction maps. Two radiologists assessed DLCT-based volume fraction maps for the presence of perifocal BME, using a Likert scale (1 = no edema; 2 = likely no edema; 3 = likely edema; 4 = edema). Accuracy, sensitivity, and specificity for the detection of BME on DLCT were analyzed using MR findings as standard of reference. For the detection of BME in patients with OO, DLCT showed a sensitivity of 0.92, a specificity of 0.94, and an accuracy of 0.92 for both radiologists. Interreader agreement for the assessment of BME with DLCT was substantial (weighted κ = 0.78; 95% CI, 0.59, 0.94). DLCT with material-specific volume fraction maps allowed accurate detection of BME in patients with OO. This may spare patients additional examinations and facilitate the diagnosis of OO.

scholarly journals Measuring Identification and Quantification Errors in Spectral CT Material Decomposition

2018 ◽  
Vol 8 (3) ◽  
pp. 467 ◽  
Author(s):  
Aamir Raja ◽  
Mahdieh Moghiseh ◽  
Christopher Bateman ◽  
Niels de Ruiter ◽  
Benjamin Schon ◽  
...  
Keyword(s):  
Spectral Ct ◽  
Material Decomposition ◽  
Identification And Quantification

Image-domain Material Decomposition for Spectral CT using a Generalized Dictionary Learning

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Weiwen Wu ◽  
Peijun Chen ◽  
Shaoyu Wang ◽  
Varut Vardhanabhuti ◽  
Fenglin Liu ◽  
...  
Keyword(s):  
Dictionary Learning ◽  
Spectral Ct ◽  
Material Decomposition ◽  
Image Domain
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