Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reliable Tuberculosis Detection using Chest X-ray with Deep Learning,
  Segmentation and Visualization   Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial
infection and is one of the top 10 leading causes of death. Accurate and early
detection of TB is very important, otherwise, it could be life-threatening. In
this work, we have detected TB reliably from the chest X-ray images using image
pre-processing, data augmentation, image segmentation, and deep-learning
classification techniques. Several public databases were used to create a
database of 700 TB infected and 3500 normal chest X-ray images for this study.
Nine different deep CNNs (ResNet18, ResNet50, ResNet101, ChexNet, InceptionV3,
Vgg19, DenseNet201, SqueezeNet, and MobileNet), which were used for transfer
learning from their pre-trained initial weights and trained, validated and
tested for classifying TB and non-TB normal cases. Three different experiments
were carried out in this work: segmentation of X-ray images using two different
U-net models, classification using X-ray images, and segmented lung images. The
accuracy, precision, sensitivity, F1-score, specificity in the detection of
tuberculosis using X-ray images were 97.07 %, 97.34 %, 97.07 %, 97.14 % and
97.36 % respectively. However, segmented lungs for the classification
outperformed than whole X-ray image-based classification and accuracy,
precision, sensitivity, F1-score, specificity were 99.9 %, 99.91 %, 99.9 %,
99.9 %, and 99.52 % respectively. The paper also used a visualization technique
to confirm that CNN learns dominantly from the segmented lung regions results
in higher detection accuracy. The proposed method with state-of-the-art
performance can be useful in the computer-aided faster diagnosis of
tuberculosis.

5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
29
The categories of this paper are: funct-an
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The categories of this paper are: hep-lat
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The categories of this paper are: cond-mat