Image based measurements of single cell mtDNA mutation load

Authors:
Amin Allalou;Frans M. Van De Rijke;Roos Jahangir Tafrechi;Anton K. Raap;Carolina Wählby
Affiliations:
Centre for Image Analysis, Uppsala University, Sweden;Department of Molecular Cell Biology, Leiden University Medical Center, The Netherlands;Department of Molecular Cell Biology, Leiden University Medical Center, The Netherlands;Department of Molecular Cell Biology, Leiden University Medical Center, The Netherlands;Centre for Image Analysis, Uppsala University, Sweden
Venue:
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Year:
2007

Citing 3
Cited 1

Distance transformations in digital images

Computer Vision, Graphics, and Image Processing
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations

IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological Image Analysis: Principles and Applications

Morphological Image Analysis: Principles and Applications

Estimating cell count and distribution in labeled histological samples using incremental cell search

Journal of Biomedical Imaging

Quantified Score

Hi-index	0.00

Visualization

Abstract

Cell cultures as well as cells in tissue always display a certain degree of variability, and measurements based on cell averages will miss important information contained in a heterogeneous population. This paper presents automated methods for image based measurements of mitochondiral DNA (mtDNA) mutations in individual cells. The mitochondria are present in the cell's cytoplasm, and each cytoplasm has to be delineated. Three different methods for segmentation of cytoplasms are compared and it is shown that automated cytoplasmic delineation can be performed 30 times faster than manual delineation, with an accuracy as high as 87%. The final image based measurements of mitochondrial mutation load are also compared to, and show high agreement with, measurements made using biochemical techniques.