# Medinoid: Computer-Aided Diagnosis and Localization of Glaucoma Using Deep Learning +
(**b**) As glaucoma advances, the field of vision of a patient slowly narrows. (**c**) Advanced glaucoma without proper treatment leads to substantial vision loss, and to blindness if left untreated. These approaches are relatively more accurate than their predecessors, while gradually reducing the time complexity. Nevertheless, when the ONH is not clearly visible in an input image, then the accuracy drops significantly [22]. A recent effort on ONH localization leveraged CNNs [27], using U-Net and polar transformations. However, this approach only segments the optic disc and the optic cup for measuring the CDR, given that the latter is considered to be an important factor for glaucoma diagnosis. We can therefore \begin{table}
\begin{tabular}{c l l l l l l l} \hline \hline
**Reference** & **Approach** & **Dataset** & **Classifier** & \multicolumn{4}{c}{**Effectiveness**} \\ \cline{4-9}  & & & **Accuracy** & **Sensitivity** & **Specificity** & **AUROC** \\ \hline
[17] & Entropy sampling, & DRISHTI-GS,50 & Softmax & 94.1\% & 92.3\% & 95.6\% & N/A \\  & ensemble learning, and & images & logistic & & & & \\  & CNNs & & classifier & & & & \\
[10] & Higher order spectra, & Private, 60 & SVM & 92\% & 90\% & 93\% & N/A \\  & trace transform, and & images & & & & & \\  & discrete wavelet & transform & & & & & \\
[11] & Pixel intensity values, & Private, 200 & Naive Bayes, & 80\% & N/A & N/A & N/A \\  & texture, spectral features, & images & & \(k\)-NN, and & & & & \\  & and histogram & & SVM & & & & \\  & parameters & & & SVM & & & \\
[13] & Wavelet feature & Private, 63 & SVM and & 94.7\% & 97.0\% & 93.3\% & N/A \\  & extraction and & images & \(k\)-NN & & & & & \\
[18] & Circular Hough & ORIGAlight, 650 & NA & CDR & N/A & N/A & N/A \\  & transform, edge & images & & error: 0.10 & & & \\  & detection, and optimum & & & & & & \\  & channel selection & & & & & & \\
[23] & Morphological & Private, 50 & NA & 96\% & N/A & N/A & N/A \\  & operations, geodesic & images & & & & & \\  & reconstruction by & & & & & & \\  & dilation & & & & & & \\
[24] & Region-based active & Private, 138 & NA & Vertical & N/A & N/A & N/A \\  & contour model, Hough & images & & CDR & & & \\  & transform, vessel bend & & & error: & & & \\  & detection, and \(t\)-bends & & & 0.09/0.08 & & & & \\  & information & & & (mean/std.); & & & \\  & & & & CDR area & & & \\  & & & ratio: & & & & \\  & & & & 0.12/0.10 & & & \\
[14] & Extraction of energy & Private, 60 & SVM, & 93\% & N/A & N/A & N/A \\  & features using a wavelet & images & & SMO, RF, & & & \\  & transform and & & & and naive & & & \\  & classification & & Bayes & & & & \\
[15] & Adaptive thresholding & Private, 67 & SVM and & 94.4\% & 100\% & 90\% & N/A \\  & and ISNT quadrants of & images & ANN & & & & \\  & neuro-retinal rim area & & & & & & \\  & and blood vessels & & & & & & \\
[16] & Morphological & Private, 61 & ANN & 90\% & 100\% & 80\% & N/A \\  & operations, thresholding, & images & & & & & \\  & and classification & & & & & & \\
[12] & Combination of texture & Private, 60 & RF & 91\% & N/A & N/A & N/A \\  & and higher order spectra & images & & & & & \\  & and classification & & & & & & \\
[25] & Fractal analysis and & N/A & SVM & 88\% & 93\% & 67\% & 82\% \\  & classification & & & & & & \\
[26] & Pixel intensity values, & Private, not & SVM & 81\% & N/A & N/A & N/A \\  & Fast Fourier Transform & specified & & & & & \\  & (FFT) coefficients, and & & & & & & \\  & B-spline coefficients & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Overview of computer-aided diagnosis for glaucoma. The dataset described covers both training and validation sets. Effectiveness results have been rounded to one decimal place, if applicable. CDR, Cup-to-Disc Ratio; SMO, Sequential Minimal Optimization; ISNT, Inferior, Superior, Nasal, Temporal. identify two drawbacks. First, from a clinical point of view, there is the possibility of having the wrong diagnosis outcome, given that a deviating CDR does not necessarily point to the presence of glaucoma.