Neighborhood-pixels algorithm combined with Sono-CT in the diagnosis of cirrhosis: an experimental study.
The goal was to investigate the role of neighborhood-pixels algorithm (NPA) in analyzing the echogram of experimental cirrhosis and the value of high frequency real-time compound imaging (Sono-CT) in improving texture analysis. A cirrhosis model was established by subcutaneously injecting CCl(4) in 80 rats. The total group of rats were divided into a control group and four treatment groups (treated for 6, 8, 10 and 12, weeks respectively). The texture of hepatic-echograms was analyzed using a "neighborhood-pixels" algorithm. Images were obtained under conventional imaging mode and Sono-CT, respectively. The second texture parameter (FP(2)) was estimated and compared in different groups and under different modes. FP(2) increased gradually with the time of treatment and group differences were significant (p < 0.01). In these groups, FP(2) was higher under Sono-CT than under conventional condition (p < 0.01) and group differences in FP(2) under both conditions were significant (p < 0.01). Thus, FP(2) measured by neighborhood-pixels algorithm can reflect the dynamic change of the texture of echogram of cirrhosis in rats and Sono-CT can improve texture analysis by neighborhood-pixels algorithm, thus facilitating the early diagnosis of cirrhosis.
Li
Rui
R
Department of Ultrasound, Southwest Hospital, Third Military Medical University, Chongqing, China.
Hua
Xing
X
Guo
Yanli
Y
Zhang
Ping
P
Guo
Aiming
A
D000465:Algorithms; D000818:Animals; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008099:Liver / Q000000981:diagnostic imaging / Q000473:pathology; D008106:Liver Cirrhosis, Experimental / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D051381:Rats; D014463:Ultrasonography