Transfer Learning Based MA Detection (TL-MAD)
M. Kalpana Devi1, M. Mary Shanthi Rani2
1M. Kalpana Devi1, Ph. D., Research Scholar ,Department of Computer Science and Application, Gandhigram Rural Institute(Deemed to be University), Gandhigram, India.
2Dr. M. Mary Shanthi Rani, Assistant Professor, Department of Computer Science and Application, Gandhigram Rural Institute (Deemed to be University), Gandhigram, India.
Manuscript received on January 25, 2020. | Revised Manuscript received on February 15, 2020. | Manuscript published on February 30, 2020. | PP: 3553-3556 | Volume-9 Issue-3, February 2020. | Retrieval Number: C5449029320/2020©BEIESP | DOI: 10.35940/ijeat.C5449.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diabetic Retinopathy (DR) is a microvascular complication of Diabetes that can lead to blindness if it is severe. Microaneurysm (MA) is the initial and main symptom of DR. In this paper, an automatic detection of DR from retinal fundus images of publicly available dataset has been proposed using transfer learning with pre-trained model VGG16 based on Convolutional Neural Network (CNN). Our method achieves improvement in accuracy for MA detection using retinal fundus images in prediction of Diabetic Retinopathy.
Keywords: Deep learning (DL), Diabetic Retinopathy (DR), Microaneurysm (MA),Convolutional Neural Networks(CNN)