In cell image sequences, due to the nonlinear and nonGaussian motion characteristics of active cells, the accurate prediction and tracking is still an unsolved problem. We applied extended Kalman particle filter (EKF-PF) here in our study, attempting to solve the problem. Firstly we confirmed the existence and positions of the active cells. Then we established a motion model and improved it via adding motion angle estimation. Next we predicted motion parameters, such as displacement, velocity, accelerated velocity and motion angle, in region centers of the cells being tracked. Finally we obtained the motion traces of active cells. There were fourteen active cells in three image sequences which have been tracked. The errors were less than 2.5 pixels when the prediction values were compared with actual values. It showed that the presented algorithm may basically reach the solution of accurate predition and tracking of the active cells.
Algorithms ; Artificial Intelligence ; Cell Movement ; Cell Tracking ; methods ; Forecasting ; Image Enhancement ; methods ; Image Interpretation, Computer-Assisted ; methods ; Models, Theoretical

Analysis of neural stem cells' movements is one of the important parts in the fields of cellular and biological research. The main difficulty existing in cells' movement study is whether the cells tracking system can simultaneously track and analyze thousands of neural stem cells (NSCs) automatically. We present a novel cells' tracking algorithm which is based on segmentation and data association in this paper, aiming to improve the tracking accuracy further in high density NSCs' image. Firstly, we adopted different methods of segmentation base on the characteristics of the two cell image sequences in our experiment. Then we formed a data association and constituted a coefficient matrix by all cells between two adjacent frames according to topological constraints. Finally we applied The Hungarian algorithm to implement inter-cells matching optimally. Cells' tracking can be achieved according to this model from the second frame to the last one in a sequence. Experimental results showed that this approaching method has higher accuracy compared with that using the topological constraints tracking alone. The final tracking accuracies of average of sequence I and sequence II have been improved 10.17% and 4%, respectively.
Algorithms ; Animals ; Cell Count ; Cell Movement ; Cell Tracking ; statistics & numerical data ; Image Processing, Computer-Assisted ; methods ; Microscopy, Fluorescence ; Models, Theoretical ; Neural Stem Cells ; cytology

PURPOSE: We aimed to investigate the effectiveness of ferritin as a contrast agent and a potential reporter gene for tracking tumor cells or macrophages in mouse cancer models. MATERIALS AND METHODS: Adenoviral human ferritin heavy chain (Ad-hFTH) was administrated to orthotopic glioma models and subcutaneous colon cancer mouse models using U87MG and HCT116 cells, respectively. Brain MR images were acquired before and daily for up to 6 days after the intracranial injection of Ad-hFTH. In the HCT116 tumor model, MR examinations were performed before and at 6, 24, and 48 h after intratumoral injection of Ad-hFTH, as well as before and every two days after intravenous injection of ferritin-labeled macrophages. The contrast effect of ferritin in vitro was measured by MR imaging of cell pellets. MRI examinations using a 7T MR scanner comprised a T1-weighted (T1w) spin-echo sequence, T2-weighted (T2w) relaxation enhancement sequence, and T2*-weighted (T2*w) fast low angle shot sequence. RESULTS: Cell pellet imaging of Ad-hFTH in vitro showed a strong negatively enhanced contrast in T2w and T2*w images, presenting with darker signal intensity in high concentrations of Fe. T2w images of glioma and subcutaneous HCT116 tumor models showed a dark signal intensity around or within the Ad-hFTH tumor, which was distinct with time and apparent in T2*w images. After injection of ferritin-labeled macrophages, negative contrast enhancement was identified within the tumor. CONCLUSION: Ferritin could be a good candidate as an endogenous MR contrast agent and a potential reporter gene that is capable of maintaining cell labeling stability and cellular safety.
Animals ; Brain Neoplasms/*diagnostic imaging/pathology ; Cell Line, Tumor ; Cell Tracking/*methods ; Colonic Neoplasms/*diagnostic imaging/pathology ; *Contrast Media/administration & dosage ; Disease Models, Animal ; Female ; *Ferritins/administration & dosage ; Genes, Reporter ; Glioma/*diagnostic imaging/pathology ; Humans ; Injections, Intravenous ; Macrophages ; Magnetic Resonance Imaging/*methods ; Male ; Mice ; Neoplasm Transplantation ; Skin Neoplasms/*diagnostic imaging/pathology ; Time Factors