Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Weakly-supervised 3D coronary artery reconstruction from two-view
  angiographic images   The reconstruction of three-dimensional models of coronary arteries is of
great significance for the localization, evaluation and diagnosis of stenosis
and plaque in the arteries, as well as for the assisted navigation of
interventional surgery. In the clinical practice, physicians use a few angles
of coronary angiography to capture arterial images, so it is of great practical
value to perform 3D reconstruction directly from coronary angiography images.
However, this is a very difficult computer vision task due to the complex shape
of coronary blood vessels, as well as the lack of data set and key point
labeling. With the rise of deep learning, more and more work is being done to
reconstruct 3D models of human organs from medical images using deep neural
networks. We propose an adversarial and generative way to reconstruct three
dimensional coronary artery models, from two different views of angiographic
images of coronary arteries. With 3D fully supervised learning and 2D weakly
supervised learning schemes, we obtained reconstruction accuracies that
outperform state-of-art techniques.

12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
13
The categories of this paper are: quant-ph
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex