Deep-learning-assisted visualization for live-cell images

TitleDeep-learning-assisted visualization for live-cell images
Publication TypeConference Proceedings
Year of Conference2017
AuthorsCheng H-C, Cardone A, Krokos E, Stoica B, Faden A, Varshney A
Conference NameIEEE International Conference on Image Processing
Date Published09/2017
Conference LocationBeijing, China
Keywordsdeep learning, live-cell images, Visualization

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
live-cell imagery datasets. The visual representations
can be used to study temporal changes in cells, such as the morphological changes in cell at various stages of life cycle.