Table 3 Results for AD-MCI binary classification task.

From: Early diagnosis of alzheimer’s disease using PET imaging and deep learning with comparative data augmentation techniques

Method

SEN

SPEC

F-measure

Precision

Balanced Accuracy

No augmentation

0.734

0.6804

0.7113

0.69

0.7072

Local Laplacian augmentation

0.6383

0.6598

0.6417

0.6452

0.649

Prewitt-edge emphasizing augmentation

0.7128

0.701

0.7053

0.6979

0.7069

Unsharp masking augmentation

0.6383

0.6804

0.6486

0.6593

0.6594

Local contrast augmentation

0.6702

0.6598

0.6632

0.6562

0.665

LoG augmentation

0.6809

0.732

0.6957

0.7111

0.7064

Ellipsoidal averaging augmentation

0.6596

0.701

0.6703

0.6813

0.6803

Prewitt-edge emphasizing + LoG augmentations

0.7021

0.6392

0.6769

0.6535

0.6707

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