204 citations · 672 across the 14 of their papers we have counts for
7 papers · 1 filter
Defining the boundaries: challenges and advances in identifying cells in microscopy images
Nodar Gogoberidze, Beth A. Cimini
Segmentation, or the outlining of objects within images, is a critical step in the measurement and analysis of cells within microscopy images. While improvements continue to be mad…
Reproducible image-based profiling with Pycytominer
Erik Serrano, Srinivas Niranj Chandrasekaran, Dave Bunten +25
Advances in high-throughput microscopy have enabled the rapid acquisition of large numbers of high-content microscopy images. Whether by deep learning or classical algorithms, imag…
The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
Jun Ma, Ronald Xie, Shamini Ayyadhury +37
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…
Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images
Marzieh Haghighi, Mario C. Cruz, Erin Weisbart +9
Various strategies for label-scarce object detection have been explored by the computer vision research community. These strategies mainly rely on assumptions that are specific to…
CellProfiler plugins -- an easy image analysis platform integration for containers and Python tools
Erin Weisbart, Callum Tromans-Coia, Barbara Diaz-Rohrer +7
CellProfiler is a widely used software for creating reproducible, reusable image analysis workflows without needing to code. In addition to the >90 modules that make up the main Ce…
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…