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Fast registration-based automatic segmentation of serial section images for high-resolution 3-D plant seed modeling

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2 Author(s)
Bollenbeck, F. ; Pattern Recognition Group, Leibniz Inst. of Plant Genetics & Crop Plant Res., Gatersleben ; Seiffert, U.

We propose a deformation-based approach for fast and robust segmentation of histological section images into multiple tissues. Derived from deformable registration techniques, it does not solely rely on information present in the image, but uses a-priori information in terms of reference segmentations. The experimental evaluation against state-of-the-art feature based classifiers demonstrates the high performance in segmentation accuracy and the effectiveness of this approach. This serves as basis for processing high-resolution serial section datasets comprising several thousand images towards three-dimensional atlases of plant organs.

Published in:

Biomedical Imaging: From Nano to Macro, 2008. ISBI 2008. 5th IEEE International Symposium on

Date of Conference:

14-17 May 2008