no code implementations • 3 Jan 2021 • Quan Liu, Isabella M. Gaeta, Mengyang Zhao, Ruining Deng, Aadarsh Jha, Bryan A. Millis, Anita Mahadevan-Jansen, Matthew J. Tyska, Yuankai Huo
Contribution: The contribution of this paper is three-fold: (1) the proposed method aggregates adversarial simulations and single-stage pixel-embedding based deep learning; (2) the method is assessed with both the cellular (i. e., HeLa cells) and subcellular (i. e., microvilli) objects; and (3) to the best of our knowledge, this is the first study to explore annotation-free instance segmentation and tracking study for microscope videos.
no code implementations • 2 Nov 2020 • Quan Liu, Isabella M. Gaeta, Mengyang Zhao, Ruining Deng, Aadarsh Jha, Bryan A. Millis, Anita Mahadevan-Jansen, Matthew J. Tyska, Yuankai Huo
Instance object segmentation and tracking provide comprehensive quantification of objects across microscope videos.
no code implementations • 22 Oct 2020 • Quan Liu, Isabella M. Gaeta, Bryan A. Millis, Matthew J. Tyska, Yuankai Huo
To match the number of objects at the micro-level, the novel fluorescence-based micro-level matching approach was presented.