Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Compartment model-based nonlinear unmixing for kinetic analysis of
  dynamic PET images   When no arterial input function is available, quantification of dynamic PET
images requires a previous step devoted to the extraction of a reference
time-activity curve (TAC). Factor analysis is often applied for this purpose.
This paper introduces a novel approach that conducts a new kind of nonlinear
factor analysis relying on a compartment model, and computes the kinetic
parameters of specific binding tissues jointly. To this end, it capitalizes on
data-driven parametric imaging methods to provide a physical description of the
underlying PET data, directly relating the specific binding with the kinetics
of the non-specific binding in the corresponding tissues. This characterization
is introduced into the factor analysis formulation to yield a novel nonlinear
unmixing model designed for PET image analysis. This model also explicitly
introduces global kinetic parameters that allow for a direct estimation of the
binding potential with respect to the free fractions in each non-specific
binding tissue. The performance of the method is evaluated on synthetic and
real data to demonstrate its potential interest.

35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
4
The categories of this paper are: cond-mat
28
The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
1
The categories of this paper are: cs
5
The categories of this paper are: gr-qc
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph