Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Fast Predictive Simple Geodesic Regression   Deformable image registration and regression are important tasks in medical
image analysis. However, they are computationally expensive, especially when
analyzing large-scale datasets that contain thousands of images. Hence, cluster
computing is typically used, making the approaches dependent on such
computational infrastructure. Even larger computational resources are required
as study sizes increase. This limits the use of deformable image registration
and regression for clinical applications and as component algorithms for other
image analysis approaches. We therefore propose using a fast predictive
approach to perform image registrations. In particular, we employ these fast
registration predictions to approximate a simplified geodesic regression model
to capture longitudinal brain changes. The resulting method is orders of
magnitude faster than the standard optimization-based regression model and
hence facilitates large-scale analysis on a single graphics processing unit
(GPU). We evaluate our results on 3D brain magnetic resonance images (MRI) from
the ADNI datasets.

18
The categories of this paper are: econ
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
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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
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
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The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
3
The categories of this paper are: physics
4
The categories of this paper are: cond-mat
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
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The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph