Fractal analysis of retinal vasculature in relation with retinal diseases - an machine learning approach

被引:1
|
作者
Venkataramani, Deepika [1 ]
Veeranan, Jeyalakshmi [1 ]
Pitchai, Latha [2 ]
机构
[1] Anna Univ, Dept ECE, Chennai, Tamil Nadu, India
[2] Govt Coll Engn, Dept EEE, Tirunelveli, Tamil Nadu, India
来源
关键词
blood vessel enhancement; Fourier fractals; diabetic retinopathy; ATHEROSCLEROSIS RISK; VESSEL CALIBER; LUNG-CANCER; CLASSIFICATION; RETINOPATHY; DIMENSION; METHODOLOGY;
D O I
10.1515/nleng-2022-0233
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Diabetic retinopathy (DR) is caused by diabetes mellitus. Vision loss occurs as a result of DR. The goal of this study was to use the DIARETDB-1, DIARETDB-0, STARE, MESSIDOR, E-ophtha-EX, and E-ophtha-MA databases to do Fourier fractal analysis and see how it is related to retinal illnesses. Following the extraction and inversion of colour channels, blood vessel augmentation was conducted. For the blood vessel enhanced image, the fractal dimension was determined. For DR patients and normal patients, measures such as standard deviation, mean, and significance were calculated. In the E-ophthaEX database, significance was realized. In the DIARETDB-1, STARE, and DIARE-TDB-0 databases, the mean fractal value for normal patients is higher than for DR patients. The STARE database's forecast of the association between fractal dimensions and various retinal disorders and the E-ophtha-EX database's accomplishment of significance are the study's main highlights. This study also improved the robustness of the blood vessel extraction there and increased the accuracy of its diagnosis.
引用
收藏
页码:411 / 419
页数:9
相关论文
共 50 条
  • [1] MODELING THE RETINAL VASCULATURE - FRACTAL APPROACH
    YOUNG, JA
    ZIPP, T
    INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE, 1992, 33 (04) : 1081 - 1081
  • [2] Robust Methodology for Fractal Analysis of the Retinal Vasculature
    Azemin, M. Z. Che
    Kumar, D. K.
    Wong, T. Y.
    Kawasaki, R.
    Mitchell, P.
    Wang, J. J.
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2011, 30 (02) : 243 - 250
  • [3] Fractal analysis of the retinal vasculature and chronic kidney disease
    Sng, Chelvin C. A.
    Sabanayagam, Charumathi
    Lamoureux, Ecosse L.
    Liu, Erica
    Lim, Su Chi
    Hamzah, Haslina
    Lee, Jeannette
    Tai, E. Shyong
    Wong, Tien Y.
    NEPHROLOGY DIALYSIS TRANSPLANTATION, 2010, 25 (07) : 2252 - 2258
  • [4] Analysis on retinal diseases using machine learning algorithms
    Mahendran, G.
    Periyasamy, M.
    Murugeswari, S.
    Devi, N. Karthika
    MATERIALS TODAY-PROCEEDINGS, 2020, 33 : 3102 - 3107
  • [5] Retinal Vasculature Fractal and Stroke Mortality
    Liew, Gerald
    Gopinath, Bamini
    White, Andrew J.
    Burlutsky, George
    Wong, Tien Yin
    Mitchell, Paul
    STROKE, 2021, 52 (04) : 1276 - 1282
  • [6] MEASURING THE FRACTAL DIMENSION OF THE RETINAL VASCULATURE
    CROSS, SS
    TALBOT, JF
    COTTON, DWK
    JOURNAL OF PATHOLOGY, 1992, 168 : A158 - A158
  • [7] A machine learning approach for automated assessment of retinal vasculature in the oxygen induced retinopathy model
    Javier Mazzaferri
    Bruno Larrivée
    Bertan Cakir
    Przemyslaw Sapieha
    Santiago Costantino
    Scientific Reports, 8
  • [8] A machine learning approach for automated assessment of retinal vasculature in the oxygen induced retinopathy model
    Mazzaferri, Javier
    Larrivee, Bruno
    Cakir, Bertan
    Sapieha, Przemyslaw
    Costantino, Santiago
    SCIENTIFIC REPORTS, 2018, 8
  • [9] Relation Between Retinal Vasculature and Retinal Thickness in Macular Edema
    Ajaz, Aqsa
    Aliahmad, Behzad
    Sarossy, Marc
    Kumar, Dinesh K.
    2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2019, : 5593 - 5596
  • [10] Retinal Vasculature Fractal Dimension Measures Vessel Density
    Ab Hamid, Fadilah
    Azemin, Mohd Zulfaezal Che
    Salam, Adzura
    Aminuddin, Amilia
    Daud, Norsyazwani Mohd
    Zahari, Ilyanoon
    CURRENT EYE RESEARCH, 2016, 41 (06) : 823 - 831