Chang Sun1, Roido Manavaki1, Jason Tarkin2, Christopher Wall2, James HF Rudd2, Fiona J Gilbert1, and Martin J Graves1
1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
1Department of Radiology, University of Cambridge, Cambridge, United Kingdom, 2Division of Cardiovascular Medicine, University of Cambridge, Cambridge, United Kingdom
A retrospective hybrid bias correction technique for thoracic
ZTE images is presented, which combines the surface fitting and histogram-based
methods. The method normalized signal intensity in the lung and reduced signal intensity
variation in tissue region.
Figure 1. The
original ZTE image (A) is bias corrected with N4ITK (ZTEN4; B) and histogram-based methods ( ZTEhist; C). PCA is applied to
the Dixon images (D-G) to extract the first two principal
components. These are input into a five-class k-means cluster (H) together
with the normalised ZTEN4 image to obtain
a lung segmentation (I). A hybrid bias field (L) is created by replacing the
lung region values in the ZTEN4 bias field (J)
with those from the ZTEhist bias field (K).
After smoothing the lung edges, a bias-corrected ZTE image (M) is calculated by dividing (A) by the
hybrid bias field (L).
Figure 3. Boxplot showing the coefficient of variation for
the body, tissue and lung regions (n = 9 patients). Subplot D illustrates the corresponding
coefficient of joint variation for tissue and lung.
