Year:2021   Volume: 3   Issue: 3   Area: Electrical, Electronics and Communications Engineering

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  3. ID: 81

Rana M. HASAN & Ielaf O. Abdul MAJJED

COMPARISON BETWEEN DIFFERENT METHODS FOR IDENTIFYING LESION IN PULMONARY X-RAY IMAGES

The image retrieval system is one of the most prevalent and challenging systems of deep learning. To perform image retrieval for lung disease radiography systems, three methods were used: Firstly, we built a convolution neural network from scratch to extract and classify features by using six convolution layers and two fully connected layers. Secondly, it trained the feature patterns and classified categories by transfer learning techniques (Resnet_50). Thirdly, by training feature patterns by (inception V3) and classifying them by Support Vector Machine (SVM). After the system retrieval set of images depending on the class labels, these methods were compared to find the most accurate and fastest method among them. The concluded from the results of our proposed system that the accuracy of CNN from scratch was better than the learning methods (96.2%), but Resnet-50 was faster than the other methods and had good accuracy (94.81%).

Keywords: CBMIR, CMIR, Deep learning, Transfer learning, CNN.

http://dx.doi.org/10.47832/2717-8234.3-3.10


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