references.bib

@inproceedings{BPDL2016,
    author="Borovec, Ji{\v{r}}{\'i}
            and Kybic, Jan",
    editor="Chen, Chu-Song
            and Lu, Jiwen
            and Ma, Kai-Kuang",
    title="Binary Pattern Dictionary Learning for Gene Expression Representation in Drosophila Imaginal Discs",
    bookTitle="Computer Vision -- ACCV 2016 Workshops: ACCV 2016 International Workshops, Taipei, Taiwan, November 20-24, 2016, Revised Selected Papers, Part II",
    year="2016",
    publisher="Springer International Publishing",
    address="Cham",
    pages="555--569",
    abstract="We present an image processing pipeline which accepts a large number of images, containing spatial expression information for thousands of genes in Drosophila imaginal discs. We assume that the gene activations are binary and can be expressed as a union of a small set of non-overlapping spatial patterns, yielding a compact representation of the spatial activation of each gene. This lends itself well to further automatic analysis, with the hope of discovering new biological relationships. Traditionally, the _images were labeled manually, which was very time consuming. The key part of our work is a binary pattern dictionary learning algorithm, that takes a set of binary _images and determines a set of patterns, which can be used to represent the input _images with a small error. We also describe the preprocessing phase, where input _images are segmented to recover the activation _images and spatially aligned to a common reference. We compare binary pattern dictionary learning to existing alternative methods on synthetic data and also show results of the algorithm on real microscopy _images of the Drosophila imaginal discs.",
    isbn="978-3-319-54427-4",
    doi="10.1007/978-3-319-54427-4_40",
    url="https://doi.org/10.1007/978-3-319-54427-4_40"
}