Accurate detection in volumetric images using elastic registration based validation

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Abstract

In this paper, we propose a method for accurate detection and segmentation of cells in dense plant tissue of Arabidopsis Thaliana. We build upon a system that uses a top down approach to yield the cell segmentations: A discriminative detection is followed by an elastic alignment of a cell template. While this works well for cells with a distinct appearance, it fails once the detection step cannot produce reliable initializations for the alignment. We propose a validation method for the aligned cell templates and show that we can thereby increase the average precision substantially.

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Mai, D., Dürr, J., Palme, K., & Ronneberger, O. (2014). Accurate detection in volumetric images using elastic registration based validation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8753, pp. 453–463). Springer Verlag. https://doi.org/10.1007/978-3-319-11752-2_37

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