Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-end lung nodule detection framework with model-based feature
  projection block   This paper proposes novel end-to-end framework for detecting suspicious
pulmonary nodules in chest CT scans. The method core idea is a new nodule
segmentation architecture with a model-based feature projection block on
three-dimensional convolutions. This block acts as a preliminary feature
extractor for a two-dimensional U-Net-like convolutional network. Using the
proposed approach along with an axial, coronal, and sagittal projection
analysis makes it possible to abandon the widely used false positives reduction
step. The proposed method achieves SOTA on LUNA2016 with 0.959 average
sensitivity, and 0.936 sensitivity if the false-positive level per scan is
0.25. The paper describes the proposed approach and represents the experimental
results on LUNA2016 as well as ablation studies.

31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
15
The categories of this paper are: nucl-ex
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
20
The categories of this paper are: acc-phys