A critical insight into pragmatic manifestation of diabetic retinopathy grading and detection
Nowadays, artificial intelligence applications invade all of the fields including medical applications field. Deep learning, a subfield of artificial intelligence, in particular, Convolutional Neural Networks (CNN), have quickly become the first choice for processing and analyzing medical images...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Blue Eyes Intelligence Engineering & Sciences Publication
2019
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/83364/1/A%20Critical%20Insight%20into%20Pragmatic%20Manifestation%20of%20Diabetic%20Retinopathy%20Grading%20and%20Detection.pdf http://irep.iium.edu.my/83364/ https://www.ijitee.org/wp-content/uploads/papers/v9i2/B8001129219.pdf |
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| Summary: | Nowadays, artificial intelligence applications invade
all of the fields including medical applications field. Deep
learning, a subfield of artificial intelligence, in particular,
Convolutional Neural Networks (CNN), have quickly become the
first choice for processing and analyzing medical images due to its
performance and effectiveness. Diabetic retinopathy is a vision
loss disease that infects people with diabetes. This disease
damages the blood vessels in the retina, hence, leads to blindness.
Due to the sensitivity and complications involved in managing
diabetics, designing and developing automated systems to detect
and grade diabetic retinopathy is considered one of the recent
research areas in the world of medical image applications. In this
paper, the aspects of deep learning field related to diabetic
retinopathy have been discussed. Various concepts in deep
learning including traditional Artificial Neural Network (ANN)
algorithm, ANN drawbacks in context of computer vision and
image processing applications, and the best algorithm to
overcome ANN drawbacks, CNN, have been elucidated along with
the architecture. The paper also reviews an extensive summary of
some works in the current research trend and future applications
of the DL algorithms in medical image analysis for DR detection
and grading. Furthermore, various research gabs related to
building such automated systems for medical image analysis have
been conferred – such as imbalance dataset which is considered
one of the main performance issues that should be handled, the
need of high performance computational resources to train deep
and efficient models and others. This is quite beneficial for
researchers working in the domain of medical image analysis to
handle DR |
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