Identifikasi Penyakit Hypertensive Retinopathy Melalui Citra Fundus Retina Menggunakan Probabilistic Neural Network
65
DAFTAR PUSTAKA
Badii,
Chitra.
2016.
Making
Sense
of
Hypertensive
Retinopathy.
http://www.healthline.com/ . Diakses 8 September 2016.
Bouman,
C.A.
2015.
Digital
Image
Processing.
https://engineering.purdue.edu/~bouman/ece637/.../ConnectComp.pdf. Diakses
4 Januari 2017.
Cavallari, M., Stamile, C., Umeton, R., Calimeri, F., Orzi, F. 2015. Novel Method for
Automated Analysis of Retinal Images: Results in Subjects with Hypertensive
Retinopathy and CADASIL. BioMed Research International 2015.
Chairani, R. 2016. Identifikasi Kesuburan Pria Melalui Kelainan Sperma
Berdasarkan Morfologi (Teratospermia) Menggunakan Invariant Moment.
Skripsi. Universitas Sumatera Utara.
Chudasama, D., Patel, T., Joshi, S. 2015. Image Segmentation using Morphological
Operation. International Journal of Computer Application 117(18) : 16-19.
Dataset Structered Analysis of the Retina http://www.ces.clemson.edu/~ahoover/stare/
Diakses 22 januari 2016.
Downie, L.E., Hodgson, L.A., D’Sylva, C., Mclntosh, R.L., Rogers, S.L., Connel, P.
& Wong, T.Y. 2013. Hypertensive retinopathy: comparing the Keith-WagenerBarker to a simplified classification. Journal of Hypertension 31(5): 960-965.
Fatihah, N. 2016. Identifikasi Jenis Kayu Tropis Menggunakan Backpropagation
Neural Network. Skripsi. Universitas Sumatera Utara.
Febriani, A. 2014. Identifikasi Diabetic Retinopathy Melalui Citra Retina
Menggunakan Modified K-Nearest Neighbor . Skripsi. Universitas Sumatera
Utara.
Hussain, M.A., Mamun, A.A., Reid, C.,
Huxley, R.R. 2016. Prevalence,
Awareness, Treatment and Control of Hypertension in Indonesian Adults Aged
Universitas Sumatera Utara
66
≥ 40 Years: Findings from the Indonesia Family Life Survey (IFLS). PLoS
ONE 11(8) : e0160922.
Hutson, N., Adkinson, J., Sidiropoulos, P., Vlachos, I., Iasemidis, L. 2016.
Classification of Ocular Disorders Based on Fractal and Invariant Moment
Analysis of Retinal Fundus Images. Southern Biomedical Engineering
Conference, pp : 57-58.
Joshi, S., Karule, P.T. 2012. Retinal Blood Vessel Segmentation. International
Journal of Engineering and Innovative Technology 1(3) : 175-178.
Kaur, R., Kaur, S. 2013. Object Extraction and Boundary Tracing Algorithms for
Digital Image Processing: Comparative Analysis: A Review. International
Journal of Advanced Research in Computer Science and Sofware Engineering
3(5):263-268.
Kementrian Kesehatan. 2013. Laporan Hasil Riset Kesehatan Dasar, RISKESDAS.
Indonesia . Jakarta.
Kementrian Kesehatan. 2014. Infodatin Hipertensi. Pusat Data dan Informasi.
Indonesia . Jakarta.
Kisan, S., Mishra, S., Mishra, S. A Survey on Applications of Fractal Dimension upon
Various Image Processing Applications. International Journal of Advanced
Research in Computer and Communication Engineering 5(9): 44-47
Lotfi, A., Benyettou, A. 2014. A reduced probabilistic neural network for the
classi_cation of large databases. Turkish Journal of Electrical Engineering &
Computer Sciences 22 : 979-989.
Mehta, K., Kaur, N. 2016. An Enhanced Segmentation Technique for Blood Vessel in
Retinal Images. International Journal of Computer Application 150(6) : 9-15.
Mishra, M., Jena.,A.R., Das, R. 2013. A Probabilistic Neural Network Approach for
Classification of Vehicle. International Journal of Application or Innovation
in Engineering & Management (IJAIEM) 2(7) : 367 -371.
Universitas Sumatera Utara
67
Narasimhan, K., Neha, V.C. & Vijayarekha, K. 2012. Hypertensive Retinopathy
Diagnosis from Fundus Images by Estimation of AVR. International
Conferences on Modelling Optimazation and Computing 38 : 980-993.
National Institutes of Health (NIH). High Blood Preasure and Eye Disease. 2014.
https://www.nih.gov/. Diakses 10 September 2016.
Noronha, K., K.T, Navya & Nayak, K. P. 2012. Support System for the Automated
Detection of Hypertensive Retinopathy using Fundus Images. International
Conferences on Eletronic Design and Signal Processing, pp 7-11.
Oktariani, A. 2016. Identifikasi Penyakit Daun Teh dengan Metode Probabilistic
Neural Network (PNN). Skripsi. Universitas Sumatera Utara.
Ong, Y.-T., Wong, T.Y., Klein, R., Klein, B.E.K., Mitchell, P., Sharrett, A.R., Couper,
D.J., & Ikram, M.K. 2013. Hypertensive Retinopathy and Risk of Stroke.
Hypertension. 62(4): 706-711.
Palomino, L.V., Jr, V.S, Neto, R.M.F. 2014. Probabilistic Neural Network and Fuzzy
Cluster Analysis Methods Applied to Impedance-Based SHM for Damage
Classifcation. Hindwai Publishing Corporation 2014(2014): 1-12.
Prakash, B., Yerpude, A. 2015. A Survey on Plant Leaf Disease Identification.
International Journal of Advanced Research in Computer Science and
Software Engineering 5(3) : 313-317.
Putra, D. 2010. Pengolahan Citra Digital. Yogyakarta : Andi.
Ramya, C., Rani, S.S., 2012. A Novel Method for the Contrast Enhancement of Fog
Degraded Video Sequences. International Journal of Coumpter Applications
54(13) : 1-5.
Shahana,S, Das, D.C.N. 2016. Probabilistic Neural Network Assisted Cell Tracking
and Classification, International Research Journal of Engineering and
Technology (IRJET) 3(8):1155-1161.
Universitas Sumatera Utara
68
Sharma, D.P. 2013. Intensity Transformation using Contrast Limited Adaptive
Histogram Equalization. International Journal of Engineering Research 2(4) :
282:285.
Singh, R.P., Dixit, M. 2015. International Journal of Signal Processing, Image
Processing and Pattern Recognition 8(8) : 345-352.
Soltani, Z., Jafarian, A. 2016. A New Artificial Neural Networks Approach for
Diagnosing Diabetes Disease Type II.
International Journal of Advanced
Computer Science and Applications 7(6) : 89-94.
You,S., Bas, E., Erdogmus, D. Principal curve based retinal vessel segmentation
towards diagnosis of retinal diseases, IEEE International Conference
Healthcare Informatics, Imaging and System Biology. 11: 331–337.
Zhou, H. & Wu, J. & Zhang, J. 2010. Digital Image Processing: Part I (1st edition).
http://bookboon.com/en/digital-image-processing-part-one-ebook . Diakses 26
Desember 2016.
Universitas Sumatera Utara
DAFTAR PUSTAKA
Badii,
Chitra.
2016.
Making
Sense
of
Hypertensive
Retinopathy.
http://www.healthline.com/ . Diakses 8 September 2016.
Bouman,
C.A.
2015.
Digital
Image
Processing.
https://engineering.purdue.edu/~bouman/ece637/.../ConnectComp.pdf. Diakses
4 Januari 2017.
Cavallari, M., Stamile, C., Umeton, R., Calimeri, F., Orzi, F. 2015. Novel Method for
Automated Analysis of Retinal Images: Results in Subjects with Hypertensive
Retinopathy and CADASIL. BioMed Research International 2015.
Chairani, R. 2016. Identifikasi Kesuburan Pria Melalui Kelainan Sperma
Berdasarkan Morfologi (Teratospermia) Menggunakan Invariant Moment.
Skripsi. Universitas Sumatera Utara.
Chudasama, D., Patel, T., Joshi, S. 2015. Image Segmentation using Morphological
Operation. International Journal of Computer Application 117(18) : 16-19.
Dataset Structered Analysis of the Retina http://www.ces.clemson.edu/~ahoover/stare/
Diakses 22 januari 2016.
Downie, L.E., Hodgson, L.A., D’Sylva, C., Mclntosh, R.L., Rogers, S.L., Connel, P.
& Wong, T.Y. 2013. Hypertensive retinopathy: comparing the Keith-WagenerBarker to a simplified classification. Journal of Hypertension 31(5): 960-965.
Fatihah, N. 2016. Identifikasi Jenis Kayu Tropis Menggunakan Backpropagation
Neural Network. Skripsi. Universitas Sumatera Utara.
Febriani, A. 2014. Identifikasi Diabetic Retinopathy Melalui Citra Retina
Menggunakan Modified K-Nearest Neighbor . Skripsi. Universitas Sumatera
Utara.
Hussain, M.A., Mamun, A.A., Reid, C.,
Huxley, R.R. 2016. Prevalence,
Awareness, Treatment and Control of Hypertension in Indonesian Adults Aged
Universitas Sumatera Utara
66
≥ 40 Years: Findings from the Indonesia Family Life Survey (IFLS). PLoS
ONE 11(8) : e0160922.
Hutson, N., Adkinson, J., Sidiropoulos, P., Vlachos, I., Iasemidis, L. 2016.
Classification of Ocular Disorders Based on Fractal and Invariant Moment
Analysis of Retinal Fundus Images. Southern Biomedical Engineering
Conference, pp : 57-58.
Joshi, S., Karule, P.T. 2012. Retinal Blood Vessel Segmentation. International
Journal of Engineering and Innovative Technology 1(3) : 175-178.
Kaur, R., Kaur, S. 2013. Object Extraction and Boundary Tracing Algorithms for
Digital Image Processing: Comparative Analysis: A Review. International
Journal of Advanced Research in Computer Science and Sofware Engineering
3(5):263-268.
Kementrian Kesehatan. 2013. Laporan Hasil Riset Kesehatan Dasar, RISKESDAS.
Indonesia . Jakarta.
Kementrian Kesehatan. 2014. Infodatin Hipertensi. Pusat Data dan Informasi.
Indonesia . Jakarta.
Kisan, S., Mishra, S., Mishra, S. A Survey on Applications of Fractal Dimension upon
Various Image Processing Applications. International Journal of Advanced
Research in Computer and Communication Engineering 5(9): 44-47
Lotfi, A., Benyettou, A. 2014. A reduced probabilistic neural network for the
classi_cation of large databases. Turkish Journal of Electrical Engineering &
Computer Sciences 22 : 979-989.
Mehta, K., Kaur, N. 2016. An Enhanced Segmentation Technique for Blood Vessel in
Retinal Images. International Journal of Computer Application 150(6) : 9-15.
Mishra, M., Jena.,A.R., Das, R. 2013. A Probabilistic Neural Network Approach for
Classification of Vehicle. International Journal of Application or Innovation
in Engineering & Management (IJAIEM) 2(7) : 367 -371.
Universitas Sumatera Utara
67
Narasimhan, K., Neha, V.C. & Vijayarekha, K. 2012. Hypertensive Retinopathy
Diagnosis from Fundus Images by Estimation of AVR. International
Conferences on Modelling Optimazation and Computing 38 : 980-993.
National Institutes of Health (NIH). High Blood Preasure and Eye Disease. 2014.
https://www.nih.gov/. Diakses 10 September 2016.
Noronha, K., K.T, Navya & Nayak, K. P. 2012. Support System for the Automated
Detection of Hypertensive Retinopathy using Fundus Images. International
Conferences on Eletronic Design and Signal Processing, pp 7-11.
Oktariani, A. 2016. Identifikasi Penyakit Daun Teh dengan Metode Probabilistic
Neural Network (PNN). Skripsi. Universitas Sumatera Utara.
Ong, Y.-T., Wong, T.Y., Klein, R., Klein, B.E.K., Mitchell, P., Sharrett, A.R., Couper,
D.J., & Ikram, M.K. 2013. Hypertensive Retinopathy and Risk of Stroke.
Hypertension. 62(4): 706-711.
Palomino, L.V., Jr, V.S, Neto, R.M.F. 2014. Probabilistic Neural Network and Fuzzy
Cluster Analysis Methods Applied to Impedance-Based SHM for Damage
Classifcation. Hindwai Publishing Corporation 2014(2014): 1-12.
Prakash, B., Yerpude, A. 2015. A Survey on Plant Leaf Disease Identification.
International Journal of Advanced Research in Computer Science and
Software Engineering 5(3) : 313-317.
Putra, D. 2010. Pengolahan Citra Digital. Yogyakarta : Andi.
Ramya, C., Rani, S.S., 2012. A Novel Method for the Contrast Enhancement of Fog
Degraded Video Sequences. International Journal of Coumpter Applications
54(13) : 1-5.
Shahana,S, Das, D.C.N. 2016. Probabilistic Neural Network Assisted Cell Tracking
and Classification, International Research Journal of Engineering and
Technology (IRJET) 3(8):1155-1161.
Universitas Sumatera Utara
68
Sharma, D.P. 2013. Intensity Transformation using Contrast Limited Adaptive
Histogram Equalization. International Journal of Engineering Research 2(4) :
282:285.
Singh, R.P., Dixit, M. 2015. International Journal of Signal Processing, Image
Processing and Pattern Recognition 8(8) : 345-352.
Soltani, Z., Jafarian, A. 2016. A New Artificial Neural Networks Approach for
Diagnosing Diabetes Disease Type II.
International Journal of Advanced
Computer Science and Applications 7(6) : 89-94.
You,S., Bas, E., Erdogmus, D. Principal curve based retinal vessel segmentation
towards diagnosis of retinal diseases, IEEE International Conference
Healthcare Informatics, Imaging and System Biology. 11: 331–337.
Zhou, H. & Wu, J. & Zhang, J. 2010. Digital Image Processing: Part I (1st edition).
http://bookboon.com/en/digital-image-processing-part-one-ebook . Diakses 26
Desember 2016.
Universitas Sumatera Utara