Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Constrained Generative Adversarial Network Ensembles for Sharable
  Synthetic Data Generation   The sharing of medical imaging datasets between institutions, and even inside
the same institution, is limited by various regulations/legal barriers.
Although these limitations are necessities for protecting patient privacy and
setting strict boundaries for data ownership, medical research projects that
require large datasets suffer considerably as a result. Machine learning has
been revolutionized with the emerging deep neural network approaches over
recent years, making the data-related limitations even a larger problem as
these novel techniques commonly require immense imaging datasets. This paper
introduces constrained Generative Adversarial Network ensembles (cGANe) to
address this problem by altering the representation of the imaging data,
whereas containing the significant information, enabling the reproduction of
similar research results elsewhere with the sharable data. Accordingly, a
framework representing the generation of a cGANe is described, and the approach
is validated for the generation of synthetic 3D brain metastatic region data
from T1-weighted contrast-enhanced MRI studies. For 90% brain metastases (BM)
detection sensitivity, our previously reported detection algorithm produced on
average 9.12 false-positive BM detections per patient after training with the
original data, whereas producing 9.53 false-positives after training with the
cGANe generated synthetic data. Although the applicability of the introduced
approach needs further validation studies with a range of medical imaging data
types, the results suggest that the BM-detection algorithm can achieve
comparable performance by using cGANe generated synthetic data. Hence, the
generalization of the proposed approach for various modalities may occur in the
near future.

18
The categories of this paper are: econ
1
The categories of this paper are: cs
27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
7
The categories of this paper are: hep-th
8
The categories of this paper are: hep-ex
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex