Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CellTrack R-CNN: A Novel End-To-End Deep Neural Network for Cell
  Segmentation and Tracking in Microscopy Images   Cell segmentation and tracking in microscopy images are of great significance
to new discoveries in biology and medicine. In this study, we propose a novel
approach to combine cell segmentation and cell tracking into a unified
end-to-end deep learning based framework, where cell detection and segmentation
are performed with a current instance segmentation pipeline and cell tracking
is implemented by integrating Siamese Network with the pipeline. Besides,
tracking performance is improved by incorporating spatial information into the
network and fusing spatial and visual prediction. Our approach was evaluated on
the DeepCell benchmark dataset. Despite being simple and efficient, our method
outperforms state-of-the-art algorithms in terms of both cell segmentation and
cell tracking accuracies.

20
The categories of this paper are: acc-phys
15
The categories of this paper are: nucl-ex
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
4
The categories of this paper are: cond-mat
12
The categories of this paper are: nucl-th
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci