Object identification and data extraction in XRII images for C-arm based surgical navigation / 中国组织工程研究

ABSTRACT

It is a key technique of C-arm based surgical navigation to recognize circular objects and extract their geometric data from XRII images. Previous methods possess low detecting & extracting accuracy and low reliability. In this paper, we proposed a hybrid object detecting algorithm. Firstly, an improved Circle Hough Transform (CHT) was used to obtain the accumulative space, and the section of the space was used to acquire a binarized image. Secondly, connected component analysis method was used to recognize circular objects and extract their areas and center coordinates. In the improved CHT, mask and integral operator were redefined. In the connected component analysis, a new circle measurement was used. Results of the study showed that the proposed algorithm possesses high detecting ratio, high detecting accuracy, and reliability.