Early diagnosis of Alzheimer’s disease using dual GAN model with pyramid attention networks

Figures & data

Table 1. Different Stages of Alzheimer’s disease.

Type of AD	Description
Preclinical	Changes that may be measured in biomarkers (such as those seen in brain imaging and spinal fluid, for example) before the appearance of symptoms
MCI	Mild changes in memory and cognition abilities, enough to be noticed and measured, but not mental retardation that compromises day-to-day activities and also functioning
Dementia	Modifications in memory and cognition that are perceptible and measurable but not severe enough to interfere with daily life and regular activities. Cognitive and behavioural changes that make it difficult to perform everyday tasks Memory, thought, and behaviour problems that make it difficult to carry out routine tasks and interact socially Signs of impaired memory, cognition, and behaviour

Table 2. Impairment Stages.

Stages	Impairment Stages
Stage 1	Impairment is nothing
Stage 2	Mild decline of cognitive issues
Stage 3	Early stage of dementia by moderate cognitive decline
Stage 4	Early mid stage dementia by moderate severe cognitive decline
Stage 5	Moderately severe cognitive stage
Stage 6	Late mid stage dementia by severe cognitive decline
Stage 7	Very severe cognitive decline for last stage dementia

Figure 1. Flowchart for Proposed Approach.

Figure 2. Pyramid Net for Feature Extraction.

Figure 3. AD Classification using Dual Training CNN and GAN.

Figure 4. Loss of the combine training model.

Figure 5. Accuracy of the model Train vs. Test.

Figure 6. Confusion Matrix.

Figure 7. ROC curve of the model.

Figure 8. Performance of our Model against conventional CNN; (a) Accuracy against Number of Samples (b) Accuracy against Error Ratio (c) Sensitivity against Number of Samples (d) Sensitivity against Error Ratio (e) Specificity (%) against Number of Samples (f) Precision against Number of Samples.

Table 3. Class average classification precisions.

Used Approach	Accuracy	Specificity	Sensitivity	Precision	F-score
SVM	82.34%	83.45%	84.56%	85.56%	83.34%
CNN	93.83%	95.69%	92.78%	94.45%	95.67%
Proposed	98.87%	98.78%	95.67%	99.78%	99.67%