Name
Abstract | ||
|---|---|---|
We propose to use particle filter [1], along with active contour [2] to track and model the plus-end tips of microtubules in confocal microscopy. Microtubules are polymers that change between states of growth, shortening, and pause. These events are critical to many cellular functions and are targets for successful cancer chemotherapy agents like Taxol. However, analyses are performed manually by researchers in most cases. Hence there is a need for a rapid and efficient quantification algorithm. In this paper, we propose to uses particle filter to track microtubule dynamics. While there are other algorithms that track microtubule movements, none of them uses inter-frame information. In our system, we use an open active contour to segment individual microtubule in each frame. Particle filter is used to track microtubule movements using information from previous frame. A simple motion and observation model is used to model the motion of microtubule movement. We show some of the results using MCF-7 breast cancer cell lines captured using fluorescent confocal microscopy and conclude that adding particle filter improves the accuracy of the system. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICIP.2007.4379879 | ICIP (5) |
Keywords | Field | DocType |
mammography,cellular function,active contour,particle filtering,biomedical optical imaging,fluorescent confocal microscopy,confocal microscopy,cancer chemotherapy agent,image segmentation,particle filter,microtubule dynamics,quantification algorithm,breast cancer cell,index terms— microtubule dynamics,medical image processing,indexing terms | Active contour model,Computer vision,Microtubule dynamics,Cancer chemotherapy,Microtubule,Computer science,Particle filter,Image segmentation,Artificial intelligence,Confocal microscopy | Conference |
Volume | ISSN | ISBN |
5 | 1522-4880 E-ISBN : 978-1-4244-1437-6 | 978-1-4244-1437-6 |
Citations | PageRank | References |
7 | 0.80 | 8 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Koon Yin Kong | 1 | 8 | 2.90 |
| Adam I. Marcus | 2 | 7 | 2.49 |
| Paraskevi Giannakakou | 3 | 7 | 1.81 |
| May D. Wang | 4 | 355 | 66.20 |