Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automated Segmentation of Cervical Nuclei in Pap Smear Images using
  Deformable Multi-path Ensemble Model   Pap smear testing has been widely used for detecting cervical cancers based
on the morphology properties of cell nuclei in microscopic image. An accurate
nuclei segmentation could thus improve the success rate of cervical cancer
screening. In this work, a method of automated cervical nuclei segmentation
using Deformable Multipath Ensemble Model (D-MEM) is proposed. The approach
adopts a U-shaped convolutional network as a backbone network, in which dense
blocks are used to transfer feature information more effectively. To increase
the flexibility of the model, we then use deformable convolution to deal with
different nuclei irregular shapes and sizes. To reduce the predictive bias, we
further construct multiple networks with different settings, which form an
ensemble model. The proposed segmentation framework has achieved
state-of-the-art accuracy on Herlev dataset with Zijdenbos similarity index
(ZSI) of 0.933, and has the potential to be extended for solving other medical
image segmentation tasks.

14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
3
The categories of this paper are: physics
16
The categories of this paper are: stat
10
The categories of this paper are: q-bio
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The categories of this paper are: eess
29
The categories of this paper are: funct-an
4
The categories of this paper are: cond-mat