microlist logo
    • Explore
      • Courses
      • Conferences & Symposia
      • eLearning
      • Software & Other Tools
      • Jobs
      • Other
    • Techniques
      • Modalities
        • Confocal Microscopy
        • Electron Microscopy
        • FLIM
        • Light Sheet Microscopy
        • Multi-photon Microscopy
        • Super-resolution Microscopy
        • TIRF
      • Methods
        • FRAP / Photoactivation
        • FRET
        • Optogenetics
        • Quantitative Microscopy
        • Volume EM (vEM)
      • Detectors
      • Fluorophores
        • Fluorescent Probes
        • Fluorescent Proteins
      • Image Analysis
        • Machine Learning
      • Live Imaging
        • In Vivo Imaging
    • Special Interest
      • Career Development
      • Diversity & Inclusion
      • Teaching Tools
      • For Core Facilities
    • Forum
    • Info
      • About
      • Contact
      • FAQ
      • Submit a Listing
    Submit a Listing
    Sign in or Register
    Submit a Listing

    Nucleaizer.org

    nuclei segmentation

    • Website
    • Tool Info
    • prev
    • next
    • Share
    • Website
    • Bookmark
    • prev
    • next
    Description

    The method uses maskRCNN, as it is described in Hollandi et al. – [BioRxiv]

    From manuscript:

    "A deep learning framework for nucleus segmentation using image style transfer

    Abstract: Single cell segmentation is typically one of the first and most crucial tasks of image-based cellular analysis. We present a deep learning approach aiming towards a truly general method for localizing nuclei across a diverse range of assays and light microscopy modalities. We outperform the 739 methods submitted to the 2018 Data Science Bowl on images representing a variety of realistic conditions, some of which were not represented in the training data. The key to our approach is to adapt our model to unseen and unlabeled data using image style transfer to generate augmented training samples. This allows the model to recognize nuclei in new and different experiments without requiring expert annotations."

    Details
    • Tool type: Image acquisition software
    • Created by: Horvath Lab

    You May Also Be Interested In

    Dragonfly (Non-Commercial Licensing)

    • Non-commercial license for Dragonfly software
    • Licensed by Object Research Systems

    Microscopy Image Browser

    • MATLAB-based software package for advanced image processing
    • Created by Ilya Belevich, Merja Joensuu, Darshan Kumar, Helena Vihinen and Eija Jokitalo

    Weka

    • Data mining with open source machine learning software
    • Created by University of Waikato

    © 2019 Microlist | All Rights Reserved

    Cart

      • Facebook
      • Twitter
      • WhatsApp
      • Telegram
      • Pinterest
      • LinkedIn
      • Tumblr
      • VKontakte
      • Mail
      • Copy link