Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning atrial fiber orientations and conductivity tensors from
  intracardiac maps using physics-informed neural networks   Electroanatomical maps are a key tool in the diagnosis and treatment of
atrial fibrillation. Current approaches focus on the activation times recorded.
However, more information can be extracted from the available data. The fibers
in cardiac tissue conduct the electrical wave faster, and their direction could
be inferred from activation times. In this work, we employ a recently developed
approach, called physics informed neural networks, to learn the fiber
orientations from electroanatomical maps, taking into account the physics of
the electrical wave propagation. In particular, we train the neural network to
weakly satisfy the anisotropic eikonal equation and to predict the measured
activation times. We use a local basis for the anisotropic conductivity tensor,
which encodes the fiber orientation. The methodology is tested both in a
synthetic example and for patient data. Our approach shows good agreement in
both cases, with an RMSE of 2.2ms on the in-silico data and outperforming a
state of the art method on the patient data. The results show a first step
towards learning the fiber orientations from electroanatomical maps with
physics-informed neural networks.

15
The categories of this paper are: nucl-ex
23
The categories of this paper are: solv-int
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
19
The categories of this paper are: eess
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex
7
The categories of this paper are: hep-th
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin