Paper Info
Title
Automated selection of uniform regions for CT image quality detection
Abstract
CT images are widely used in pathology detection and follow-up treatment procedures. Accurate identification of pathological features requires diagnostic quality CT images with minimal noise and artifact variation. In this work, a novel Fourier-transform based metric for image quality (IQ) estimation is presented that correlates to additive CT image noise. There is presently a need to optimize contrast enhancement to ensure As Low As Reasonably Achievable (ALARA) dosage with diagnostic IQ. In the proposed method, two windowed CT image subset regions are analyzed together to identify the extent of variation in the corresponding Fourier-domain spectrum. The two square windows are chosen such that their center pixels coincide and one window is a subset of the other. The Fourier-domain spectral difference between these two sub-sampled windows is then used to isolate spatial regions-of-interest (ROI) with low variation (ROI-LV) and high variation (ROI-HV), respectively. Finally, the number of pixels within the spatial ROI-LV is correlated with image acquisition parameters that serve as IQ metrics. We observe that the number of pixels in thresholded ROI-LV regions strongly correlate with the imaging tube current (in mA) in phantom CT images (r = 0.9648, p = 0.0018, R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.9308) and patient abdominal CT images (r = 0.9283, R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.8617). Thus, the proposed method can be useful to quantitatively estimate the diagnostic CT image quality.
Year
DOI
Venue
2016
10.1109/ACSSC.2016.7869040
2016 50th Asilomar Conference on Signals, Systems and Computers
Keywords
DocType
Volume
Computed tomography,region of interest,Fourier-domain representation,noise estimation
Conference
abs/1608.04381
ISSN
ISBN
Citations 
1058-6393
978-1-5386-3955-9
1
PageRank 
References 
Authors
0.37
1
3
Name
Order
Citations
PageRank
Maitham D. Naeemi110.37
Adam M. Alessio2337.95
Sohini Roychowdhury3848.03