Novel risk index for the identification of age-related macular degeneration using radon transform and DWT features.
Age-related Macular Degeneration (AMD) affects the central vision of aged people. It can be diagnosed due to the presence of drusen, Geographic Atrophy (GA) and Choroidal Neovascularization (CNV) in the fundus images. It is labor intensive and time-consuming for the ophthalmologists to screen these images. An automated digital fundus photography based screening system can overcome these drawbacks. Such a safe, non-contact and cost-effective platform can be used as a screening system for dry AMD. In this paper, we are proposing a novel algorithm using Radon Transform (RT), Discrete Wavelet Transform (DWT) coupled with Locality Sensitive Discriminant Analysis (LSDA) for automated diagnosis of AMD. First the image is subjected to RT followed by DWT. The extracted features are subjected to dimension reduction using LSDA and ranked using t-test. The performance of various supervised classifiers namely Decision Tree (DT), Support Vector Machine (SVM), Probabilistic Neural Network (PNN) and k-Nearest Neighbor (k-NN) are compared to automatically discriminate to normal and AMD classes using ranked LSDA components. The proposed approach is evaluated using private and public datasets such as ARIA and STARE. The highest classification accuracy of 99.49%, 96.89% and 100% are reported for private, ARIA and STARE datasets. Also, AMD index is devised using two LSDA components to distinguish two classes accurately. Hence, this proposed system can be extended for mass AMD screening.
Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore; Department of Biomedical Engineering, School of Science and Technology, SIM University, 599491, Singapore; Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, 50603, Malaysia.
U Rajendra
UR
Acharya
Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore. Electronic address: mkm2@np.edu.sg.
Muthu Rama Krishnan
MR
Mookiah
Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore.
Joel E W
JE
Koh
Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore.
Jen Hong
JH
Tan
Department of Electronics and Telecommunication, St. Francis Institute of Technology, Mumbai 400103, India.
Kevin
K
Noronha
Department of Ophthalmology, Kasturba Medical College, Manipal 576104, India.
Sulatha V
SV
Bhandary
Department of Ophthalmology, Kasturba Medical College, Manipal 576104, India.
A Krishna
AK
Rao
Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore.
Yuki
Y
Hagiwara
Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, 599489, Singapore.
Chua Kuang
CK
Chua
National Healthcare Group Eye Institute, Tan Tock Seng Hospital, 308433, Singapore.
Augustinus
A
Laude
D000465:Algorithms; D020256:Choroidal Neovascularization / Q000000981:diagnostic imaging*; D016208:Databases, Factual; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008268:Macular Degeneration / Q000000981:diagnostic imaging*; D008297:Male; D018570:Risk Assessment; D060388:Support Vector Machine
Age-related macular degeneration; Computed aided diagnosis; Discrete wavelet transform; Fundus imaging; Locality sensitive discriminant analysis; Radon transform