Instruct: Identify the main category of Biorxiv papers based on the titles and abstracts
Query: DeepSea: An efficient deep learning model for automated cell segmentation and tracking Time-lapse microscopy can directly capture the dynamics and heterogeneity of cellular processes at the single-cell level. Successful application of single-cell live microscopy requires automated segmentation and tracking of hundreds of individual cells over several time points. Recently, deep learning models have ushered in a new era in quantitative analysis of microscopy images. This work presents a versatile and trainable deep-learning-based software, termed DeepSea, that allows for both segmentation and tracking of single cells and their nuclei in sequences of phase-contrast live microscopy images. We show that DeepSea can quantify several cell biological features of mouse embryonic stem cells, such as cell division cycle, mitosis, cell morphology, and cell size, with high precision using phase-contrast images. Using DeepSea, we were able to show that despite their ultrafast cell division cycle, mouse embryonic stem cells exhibit cell size control in the G1 phase of the cell cycle.
27
The categories of this paper are: pathology
9
The categories of this paper are: synthetic
10
The categories of this paper are: and
11
The categories of this paper are: cognition
17
The categories of this paper are: molecular
24
The categories of this paper are: cancer
6
The categories of this paper are: plant
20
The categories of this paper are: pharmacology
28
The categories of this paper are: communication
8
The categories of this paper are: genomics
13
The categories of this paper are: animal
25
The categories of this paper are: bioengineering
0
The categories of this paper are: genetics
12
The categories of this paper are: behavior
1
The categories of this paper are: bioinformatics
5
The categories of this paper are: cell