Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multilevel Thresholding Segmentation of T2 weighted Brain MRI images
  using Convergent Heterogeneous Particle Swarm Optimization   This paper proposes a new image thresholding segmentation approach using the
heuristic method, Convergent Heterogeneous Particle Swarm Optimization
algorithm. The proposed algorithm incorporates a new strategy of searching the
problem space by dividing the swarm into subswarms. Each subswarm particles
search for better solution separately lead to better exploitation while they
cooperate with each other to find the best global position. The consequence of
the aforementioned cooperation is better exploration, convergence and it able
the algorithm to jump from local optimal solution to the better spots. A
practical application of this method is demonstrated for the problem of medical
image thresholding segmentation. We considered two classical thresholding
techniques of Otsu and Kapur separately as the objective function for the
optimization method and applied on a set of brain MR images. Comparative
experimental results reveal that the proposed method outperforms another state
of the art method from the literature in terms of accuracy, computation time
and stable results.

23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
27
The categories of this paper are: comp-gas
32
The categories of this paper are: atom-ph
19
The categories of this paper are: eess
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con