A Deep Look Into -- Automated Lung X-Ray Abnormality Detection System
Nagullas KS Vivekanand. V Narayana Darapaneni Anwesh R P
Introduction: Automated Lung X-Ray Abnormality Detection System is the
application which distinguish the normal x-ray images from infected x-ray
images and highlight area considered for prediction, with the recent pandemic a
need to have a non-conventional method and faster detecting diseases, for which
X ray serves the purpose. Obectives: As of current situation any viral disease
that is infectious is potential pandemic, so there is need for cheap and early
detection system. Methods: This research will help to eases the work of expert
to do further analysis. Accuracy of three different preexisting models such as
DenseNet, MobileNet and VGG16 were high but models over-fitted primarily due to
black and white images. Results: This led to building up new method such as as
V-BreathNet which gave more than 96% percent accuracy. Conclusion: Thus, it can
be stated that not all state-of art CNN models can be used on B/W images. In
conclusion not all state-of-art CNN models can be used on B/W images.