| 1. |
- Althoff, Karin, 1974, et al.
(författare)
-
Combined segmentation and tracking of neural stem-cells
- 2005
-
Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 1611-3349 .- 0302-9743. ; 3540, s. 282-291
-
Tidskriftsartikel (refereegranskat)abstract
- In this paper we analyze neural stem/progenitor cells in an time-lapse image sequence. By using information about the previous positions of the cells, we are able to make a. better selection of possible cells out of a collection of blob-like objects. As a blob detector we use Laplacian of Gaussian (LoG) filters at multiple scales, and the cell contours of the selected cells are segmented using dynamic programming. After the segmentation process the cells are tracked in the sequence using a. combined nearest-neighbor and correlation matching technique. An evaluation of the system show that 95% of the cells were correctly segmented and tracked between consecutive frames.
|
|
| 2. |
|
|
| 3. |
- Althoff, Karin, 1974
(författare)
-
Segmentation and Tracking Algorithms for in Vitro Cell Migration Analysis
- 2005
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis describes a system for automatic in vitro cell migration analysis. Image sequences of adult neural stem/progenitor cells were acquired using a time-lapse bright-field microscopy setup. The adult neural stem/progenitor cell has the ability to differentiate into three different neural lineages; neuronal, astrocytic and oligodendrocytic. Different image analysis techniques were investigated for segmenting the cells in the images, such as watershed segmentation and boundary detection using dynamic programming. Some segmentation techniques required the positions of the cells to be detected first. This was done either using a multi-scale Laplace of Gaussian (LoG) filter, which detects blob-like objects in an image, or using the extended h-maxima transform. It was found that the performance of the multi-scale LoG-filter as a cell detector could be increased by using information about the cells-positions in the previous image. To track the individual cells through the sequence, the segmented cells in two consecutive images were associated using Bertsekas modified auction algorithm. The association weights were calculated based on distance, correlation and size between possible matching cells. A comparison of three different segmentation methods, evaluated after completing the tracking step, showed that the best system was an algorithm consisting of a multi-scale LoG-filter, followed by cell border detection using dynamic programming. Using that system, 93 % of the cell-to-cell associations in the evaluated sequences were correct. The obtained cell movement data was used for statistical modelling of the cell migration patterns. Using a Hidden Markov Model with two states, it was found that the motion of the glial progenitor cell was random 2/3 of the time, while the type-2 astrocyte showed a directed movement 2/3 of the time. This finding indicates possibilities for cell-type specific identification and cell sorting of live cells based on specific movement patterns in individual cell population, which would have a valuable application in neurobiological research.
|
|
| 4. |
- Althoff, Karin, 1974, et al.
(författare)
-
Tracking Contrast in Echocardiography by a Combined Snake and Optical Flow Technique
- 2000
-
Ingår i: IEEE Conf. on Computers in Cardiology. ; 27
-
Konferensbidrag (refereegranskat)abstract
- Contrast-echocardiography in conjunction with real-time video-densiometry can be an effective means of studying right ventricular (RV) structural changes, e.g. in patients diagnosed with Arrhythmogenic Right Ventricular Dysplasia (ARVD). In order to characterize RV flow pattern it may be necessary to track the front of the contrast agent as it enters the RV. Active contour models (ACM) is a standard image analysis method,which can be applied to time-dynamic tracking problem.To improve tracking speed we extended the formulationof ACM by including an additional force, derived fromthe optical flow field, another standard image analysisalgorithm. This reduced the number of iterations needed to find the front of the contrast agent significantly. Also the changes in intensity of the contrast agent over time were studied. Two groups were compared, one with30 patients diagnosed with ARVD and one with 18healthy volunteers. Our study shows that that using our suggested method (calculating wash-in and wash-out time indices) it is possible to discriminate between thetwo groups.
|
|
| 5. |
- Degerman, Johan, 1976, et al.
(författare)
-
An automatic system for in vitro cell migration studies
- 2009
-
Ingår i: Journal of Microscopy. - : Wiley. - 0022-2720 .- 1365-2818. ; 233:1, s. 178-191
-
Tidskriftsartikel (refereegranskat)abstract
- This paper describes a system for in vitro cell migration analysis. Adult neural stem/progenitor cells are studied using time-lapse bright-field microscopy and thereafter stained immunohistochemically to find and distinguish undifferentiated glial progenitor cells and cells having differentiated into type-1 or type-2 astrocytes. The cells are automatically segmented and tracked through the time-lapse sequence. An extension to the Chan-Vese Level Set segmentation algorithm, including two new terms for specialized growing and pruning, made it possible to resolve clustered cells, and reduced the tracking error by 65%. We used a custom-built manual correction module to form a ground truth used as a reference for tracked cells that could be identified from the fluorescence staining. On average, the tracks were correct 95% of the time, using our new segmentation. The tracking, or association of segmented cells, was performed using a 2-state Hidden Markov Model describing the random behaviour of the cells. By re-estimating the motion model to conform with the segmented data we managed to reduce the number of tracking parameters to essentially only one. Upon characterization of the cell migration by the HMM state occupation function, it was found that glial progenitor cells were moving randomly 2/3 of the time, while the type-2 astrocytes showed a directed movement 2/3 of the time. This finding indicates possibilities for cell-type specific identification and cell sorting of live cells based on specific movement patterns in individual cell populations, which would have valuable applications in neurobiological research.
|
|
| 6. |
|
|
