Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Novel Extension to Fuzzy Connectivity for Body Composition Analysis:
  Applications in Thigh, Brain, and Whole Body Tissue Segmentation   Magnetic resonance imaging (MRI) is the non-invasive modality of choice for
body tissue composition analysis due to its excellent soft tissue contrast and
lack of ionizing radiation. However, quantification of body composition
requires an accurate segmentation of fat, muscle and other tissues from MR
images, which remains a challenging goal due to the intensity overlap between
them. In this study, we propose a fully automated, data-driven image
segmentation platform that addresses multiple difficulties in segmenting MR
images such as varying inhomogeneity, non-standardness, and noise, while
producing high-quality definition of different tissues. In contrast to most
approaches in the literature, we perform segmentation operation by combining
three different MRI contrasts and a novel segmentation tool which takes into
account variability in the data. The proposed system, based on a novel affinity
definition within the fuzzy connectivity (FC) image segmentation family,
prevents the need for user intervention and reparametrization of the
segmentation algorithms. In order to make the whole system fully automated, we
adapt an affinity propagation clustering algorithm to roughly identify tissue
regions and image background. We perform a thorough evaluation of the proposed
algorithm's individual steps as well as comparison with several approaches from
the literature for the main application of muscle/fat separation. Furthermore,
whole-body tissue composition and brain tissue delineation were conducted to
show the generalization ability of the proposed system. This new automated
platform outperforms other state-of-the-art segmentation approaches both in
accuracy and efficiency.

21
The categories of this paper are: adap-org
9
The categories of this paper are: nlin
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga
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The categories of this paper are: math-ph
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex