Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: CASED: Curriculum Adaptive Sampling for Extreme Data Imbalance   We introduce CASED, a novel curriculum sampling algorithm that facilitates
the optimization of deep learning segmentation or detection models on data sets
with extreme class imbalance. We evaluate the CASED learning framework on the
task of lung nodule detection in chest CT. In contrast to two-stage solutions,
wherein nodule candidates are first proposed by a segmentation model and
refined by a second detection stage, CASED improves the training of deep nodule
segmentation models (e.g. UNet) to the point where state of the art results are
achieved using only a trivial detection stage. CASED improves the optimization
of deep segmentation models by allowing them to first learn how to distinguish
nodules from their immediate surroundings, while continuously adding a greater
proportion of difficult-to-classify global context, until uniformly sampling
from the empirical data distribution. Using CASED during training yields a
minimalist proposal to the lung nodule detection problem that tops the LUNA16
nodule detection benchmark with an average sensitivity score of 88.35%.
Furthermore, we find that models trained using CASED are robust to nodule
annotation quality by showing that comparable results can be achieved when only
a point and radius for each ground truth nodule are provided during training.
Finally, the CASED learning framework makes no assumptions with regard to
imaging modality or segmentation target and should generalize to other medical
imaging problems where class imbalance is a persistent problem.

31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
27
The categories of this paper are: comp-gas
28
The categories of this paper are: alg-geom
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat