A comparative study of three CT and MRI registration algorithms in nasopharyngeal carcinoma.
OBJECTIVE
To evaluate the image registration accuracy and efficiency of CT and MRI fusion using three algorithms in nasopharyngeal carcinoma (NPC).


METHODS
Twelve sets of CT and MRI scans of 12 NPC patients were fused using three image registration algorithms, respectively: Mark-and-link, Interactive, and Normalized Mutual Information (NMI). Registration accuracy was evaluated by performing statistical analysis of the coordinate differences between CT and MR anatomical landmarks along the x-, y- and z-axes. The time required to complete the registration process using three algorithms was also recorded. One-way ANOVA was used to analyze the difference of the three registration methods.


RESULTS
The mean time required for CT/MRI registration using the three different registration algorithms, mark-and-link, interactive, and NMI, was 6.25 min, 5.25 min, and 5.15 min, respectively. The mark-and-link method was more time consuming (F=8.74, p=0.001); however no statistical difference was found between the time required using interactive and NMI methods (p=0.77). Mean registration errors of the three methods along the x-axis were 0.66 mm, 0.70 mm, and 0.68 mm, respectively (F=0.09, p=0.91). Along the y-axis, the mean registration errors were 1.03 mm, 1.04 mm, and 1.03 mm, respectively (F=0.02, p=0.98). Along the z-axis, they were 0.58 mm, 0.64 mm, and 0.56 mm, respectively (F=0.21, p=0.81).


CONCLUSIONS
All three registration algorithms, mark-and-link, interactive, and NMI, can provide accurate CT/MRI registration. However the mark-and-link method was most time consuming.
Wang
XiaoShen
X
Department of Radiation Oncology, Cancer Hospital, Fudan University, Shanghai, People's Republic of China, 200032.
Li
LongGen
L
Department of Radiation Oncology, Cancer Hospital, Fudan University, Shanghai, People's Republic of China, 200032.
Hu
ChaoSu
C
Department of Radiation Oncology, Cancer Hospital, Fudan University, Shanghai, People's Republic of China, 200032.
Qiu
JianJian
J
Department of Radiation Oncology, Cancer Hospital, Fudan University, Shanghai, People's Republic of China, 200032.
Xu
ZhiYong
Z
Department of Radiation Oncology, Cancer Hospital, Fudan University, Shanghai, People's Republic of China, 200032.
Feng
Yan
Y
Department of Radiation Oncology, Cancer Hospital, Fudan University, Shanghai, People's Republic of China, 200032.
D000465:Algorithms; D002277:Carcinoma / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009303:Nasopharyngeal Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D009305:Nasopharynx / Q000000981:diagnostic imaging / Q000473:pathology; D011880:Radiotherapy Planning, Computer-Assisted; D014057:Tomography, X-Ray Computed / Q000379:methods*