Bias image correction via stationarity maximization

Authors:
T. Dorval;A. Ogier;A. Genovesio
Affiliations:
Image Mining Group, Institut Pasteur Korea, Seoul, Korea;Image Mining Group, Institut Pasteur Korea, Seoul, Korea;Image Mining Group, Institut Pasteur Korea, Seoul, Korea
Venue:
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Year:
2007

Citing 1
Cited 1

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A novel material decomposition algorithm for multienergy x-ray radiography systems

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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.