Filter By:

Journal Check one or more journals to show results from those journals only.

Choose more journals

Article type Check one or more article types to show results from those article types only.
Subject Check one or more subjects to show results from those subjects only.
Date Choose a date option to show results from those dates only.

Custom date range

Clear all filters
Sort by:
Showing 1–6 of 6 results
Advanced filters: Author: Susanne M. Rafelski Clear advanced filters
  • Cells are highly complex structures, but where does this complexity come from? Self-organization principles combined with simple physical constraints seem to control organelle size, number, shape and position. These factors then combine to give rise to the overall cell architecture.

    • Susanne M. Rafelski
    • Wallace F. Marshall
    Reviews
    Nature Reviews Molecular Cell Biology
    Volume: 9, P: 593-602
  • A dataset of 3D images from more than 200,000 human induced pluripotent stem cells is used to develop a framework to analyse cell shape and the location and organization of major intracellular structures.

    • Matheus P. Viana
    • Jianxu Chen
    • Susanne M. Rafelski
    ResearchOpen Access
    Nature
    Volume: 613, P: 345-354
  • A key step toward biologically interpretable analysis of microscopy image-based assays is rigorous quantitative validation with metrics appropriate for the particular application in use. Here we describe this challenge for both classical and modern deep learning-based image analysis approaches and discuss possible solutions for automating and streamlining the validation process in the next five to ten years.

    • Jianxu Chen
    • Matheus P. Viana
    • Susanne M. Rafelski
    Comments & Opinion
    Nature Methods
    Volume: 20, P: 968-970
  • This Perspective presents a reliable and comprehensive source of information on pitfalls related to validation metrics in image analysis, with an emphasis on biomedical imaging.

    • Annika Reinke
    • Minu D. Tizabi
    • Lena Maier-Hein
    Reviews
    Nature Methods
    Volume: 21, P: 182-194