Point-supervised segmentation of microscopy images and volumes via objectness regularization

Shijie Li, Neel Dey, Katharina Bermond, Leon Von Der Emde, Christine A. Curcio, Thomas Ach, Guido Gerig

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Annotation is a major hurdle in the semantic segmentation of microscopy images and volumes due to its prerequisite expertise and effort. This work enables the training of semantic segmentation networks on images with only a single point for training per instance, an extreme case of weak supervision which drastically reduces the burden of annotation. Our approach has two key aspects: (1) we construct a graph-theoretic soft-segmentation using individual seeds to be used within a regularizer during training and (2) we use an objective function that enables learning from the constructed soft-labels. We achieve competitive results against the state-of-the-art in point-supervised semantic segmentation on challenging datasets in digital pathology. Finally, we scale our methodology to point-supervised segmentation in 3D fluorescence microscopy volumes, obviating the need for arduous manual volumetric delineation. Our code is freely available.

    Original languageEnglish (US)
    Title of host publication2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021
    PublisherIEEE Computer Society
    Pages1558-1562
    Number of pages5
    ISBN (Electronic)9781665412469
    DOIs
    StatePublished - Apr 13 2021
    Event18th IEEE International Symposium on Biomedical Imaging, ISBI 2021 - Nice, France
    Duration: Apr 13 2021Apr 16 2021

    Publication series

    NameProceedings - International Symposium on Biomedical Imaging
    Volume2021-April
    ISSN (Print)1945-7928
    ISSN (Electronic)1945-8452

    Conference

    Conference18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
    Country/TerritoryFrance
    CityNice
    Period4/13/214/16/21

    Keywords

    • Digital pathology
    • Fluorescence microscopy
    • Semantic segmentation
    • Weak supervision

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Radiology Nuclear Medicine and imaging

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