Apoptosis detection for adherent cell populations in time-lapse phase-contrast microscopy images

Authors:
Seungil Huh;Dai Fei Elmer Ker;Hang Su;Takeo Kanade
Affiliations:
Robotics Institute, Carnegie Mellon University;Department of Orthopedic Surgery, Stanford University;Robotics Institute, Carnegie Mellon University;Robotics Institute, Carnegie Mellon University
Venue:
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Year:
2012

Citing 3
Cited 0

Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns

IEEE Transactions on Pattern Analysis and Machine Intelligence
Hidden Conditional Random Fields

IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection of mitosis within a stem cell population of high cell confluence in phase-contrast microscopy images

CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

The detection of apoptosis, or programmed cell death, is important to understand the underlying mechanism of cell development. At present, apoptosis detection resorts to fluorescence or colorimetric assays, which may affect cell behavior and thus not allow long-term monitoring of intact cells. In this work, we present an image analysis method to detect apoptosis in time-lapse phase-contrast microscopy, which is non-destructive imaging. The method first detects candidates for apoptotic cells based on the optical principle of phase-contrast microscopy in connection with the properties of apoptotic cells. The temporal behavior of each candidate is then examined in its neighboring frames in order to determine if the candidate is indeed an apoptotic cell. When applied to three C2C12 myoblastic stem cell populations, which contain more than 1000 apoptosis, the method achieved around 90% accuracy in terms of average precision and recall.