Deep-learning-assisted visualization for live-cell images
| Title | Deep-learning-assisted visualization for live-cell images |
| Publication Type | Conference Proceedings |
| Year of Conference | 2017 |
| Authors | Cheng H-C, Cardone A, Krokos E, Stoica B, Faden A, Varshney A |
| Conference Name | IEEE International Conference on Image Processing |
| Date Published | 09/2017 |
| Publisher | IEEE |
| Conference Location | Beijing, China |
| Keywords | deep learning, live-cell images, Visualization |
| Abstract | Analyzing live-cell images is particularly challenging because cells move at the same time they undergo systematic changes. Visually inspecting live-cell images therefore involves simultaneously tracking individual cells and detecting relevant spatio-temporal changes. The high cognitive burden of such a complex task makes this kind of analysis inefficient and error-prone. In this paper we describe a deep-learning-assisted visualization based on automatically derived high-level features to identify target cell changes in live-cell images. Applying a novel user-mediated color assignment scheme that maps abstract features into corresponding colors, we create color-based visual annotations that facilitate visual reasoning and analysis of complex time varying |