Bias image correction via stationarity maximization

T Dorval; A Ogier; A Genovesio

doi:10.1007/978-3-540-75759-7_84

Bias image correction via stationarity maximization

Med Image Comput Comput Assist Interv. 2007;10(Pt 2):693-700. doi: 10.1007/978-3-540-75759-7_84.

Authors

T Dorval¹, A Ogier, A Genovesio

Affiliation

¹ Image Mining Group, Institut Pasteur Korea, 39-1, Hawolgok-dong, Seongbuk-gu, Seoul 136-791, Korea.

PMID: 18044629
DOI: 10.1007/978-3-540-75759-7_84

Abstract

Automated acquisitions in microscopy may come along with strong illumination artifacts due to poor physical imaging conditions. Such artifacts obviously have direct consequences on the efficiency of an image analysis algorithm and on the quantitative measures. In this paper, we propose a method to correct illumination artifacts on biological images. This correction is based on orthogonal polynomial modeling, combined with stationary maximization criteria. To validate the proposed method we show that we improve particle detection algorithm.

MeSH terms

Algorithms*
Artifacts*
Computer Simulation
Data Interpretation, Statistical
Image Enhancement / methods*
Image Interpretation, Computer-Assisted / methods*
Likelihood Functions
Microscopy / methods*
Models, Biological
Models, Statistical
Reproducibility of Results
Sensitivity and Specificity
Stochastic Processes