Study on Medical Micro-Image Mosaic with SIFT Features
In order to obtain panoramic view of medical micro-image in remote medical diagnosis system, we should mosaic micro-image sequence accurately in remote node. SIFT features are invariant to image scaling, rotation and translation. The aim of this study is to mosaic micro-image sequence by extracting SIFT features. Firstly, search coordinate of potential features through Gaussian pyramid (with 7 octaves × 6 scales) and then filter pseudo-keypoints. Secondly, describe these features with 128-D vector. The next step is to calculate matching keypoint pairs between two time-successive images according to minimum Euclidean distance. In this step, standard deviation comparing is proposed to eliminate wrong matching pairs and appropriate threshold(8000) through experiment is used to insure matching pairs. Then, construct image motion equation considering rotation and translation and compute motion parameter by solving equation according matching pairs. Finally mosaic all images. These steps are applied in 5 micro-image sequences such as slices of lung tissue, spleen, kidney, frog blood cell and sunflower tissue. The experiment results show that the gap between two images is vanishing and the proposed method can satisfy with medical micro-images sequence mosaic.
Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo
Y. G. Wang et al., "Study on Medical Micro-Image Mosaic with SIFT Features", Advanced Materials Research, Vols. 121-122, pp. 476-481, 2010