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Apoptosis detection for non-adherent cells in time-lapse phase contrast microscopy.
- Source :
-
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention [Med Image Comput Comput Assist Interv] 2013; Vol. 16 (Pt 2), pp. 59-66. - Publication Year :
- 2013
-
Abstract
- This paper proposes a vision-based method for detecting apoptosis (programmed cell death), which is essential for non-perturbative monitoring of cell expansion. Our method targets non-adherent cells, which float or are suspended freely in the culture medium-in contrast to adherent cells, which are attached to a petri dish. The method first detects cell regions and tracks them over time, resulting in the construction of cell tracklets. For each of the tracklets, visual properties of the cell are then examined to know whether and when the tracklet shows a transition from a live cell to a dead cell, in order to determine the occurrence and timing of a cell death event. For the validation, a transductive learning framework is adopted to utilize unlabeled data in addition to labeled data. Our method achieved promising performance in the experiments with hematopoietic stem cell (HSC) populations, which are currently in clinical use for rescuing hematopoietic function during bone marrow transplants.
- Subjects :
- Algorithms
Cell Adhesion
Cells, Cultured
Humans
Image Enhancement methods
Image Interpretation, Computer-Assisted methods
Reproducibility of Results
Sensitivity and Specificity
Apoptosis physiology
Cell Tracking methods
Hematopoietic Stem Cells cytology
Hematopoietic Stem Cells physiology
Microscopy, Phase-Contrast methods
Pattern Recognition, Automated methods
Time-Lapse Imaging methods
Subjects
Details
- Language :
- English
- Volume :
- 16
- Issue :
- Pt 2
- Database :
- MEDLINE
- Journal :
- Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
- Publication Type :
- Academic Journal
- Accession number :
- 24579124
- Full Text :
- https://doi.org/10.1007/978-3-642-40763-5_8