TY - JOUR
T1 - Age-related Macular Degeneration detection using deep convolutional neural network
AU - Tan, Jen Hong
AU - Bhandary, Sulatha V.
AU - Sivaprasad, Sobha
AU - Hagiwara, Yuki
AU - Bagchi, Akanksha
AU - Raghavendra, U.
AU - Krishna Rao, A.
AU - Raju, Biju
AU - Shetty, Nitin Shridhara
AU - Gertych, Arkadiusz
AU - Chua, Kuang Chua
AU - Acharya, U. Rajendra
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Age-related Macular Degeneration (AMD) is an eye condition that affects the elderly. Further, the prevalence of AMD is rising because of the aging population in the society. Therefore, early detection is necessary to prevent vision impairment in the elderly. However, organizing a comprehensive eye screening to detect AMD in the elderly is laborious and challenging. To address this need, we have developed a fourteen-layer deep Convolutional Neural Network (CNN) model to automatically and accurately diagnose AMD at an early stage. The performance of the model was evaluated using the blindfold and ten-fold cross-validation strategies, for which the accuracy of 91.17% and 95.45% were respectively achieved. This new model can be utilized in a rapid eye screening for early detection of AMD in the elderly. It is cost-effective and highly portable, hence, it can be utilized anywhere.
AB - Age-related Macular Degeneration (AMD) is an eye condition that affects the elderly. Further, the prevalence of AMD is rising because of the aging population in the society. Therefore, early detection is necessary to prevent vision impairment in the elderly. However, organizing a comprehensive eye screening to detect AMD in the elderly is laborious and challenging. To address this need, we have developed a fourteen-layer deep Convolutional Neural Network (CNN) model to automatically and accurately diagnose AMD at an early stage. The performance of the model was evaluated using the blindfold and ten-fold cross-validation strategies, for which the accuracy of 91.17% and 95.45% were respectively achieved. This new model can be utilized in a rapid eye screening for early detection of AMD in the elderly. It is cost-effective and highly portable, hence, it can be utilized anywhere.
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U2 - 10.1016/j.future.2018.05.001
DO - 10.1016/j.future.2018.05.001
M3 - Article
AN - SCOPUS:85047186810
SN - 0167-739X
VL - 87
SP - 127
EP - 135
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -