DICOM -UNET Computer Vision Dataset
325 Total Images
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Dataset Split
Train Set 92%
300Images
Valid Set 8%
25Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 1024x1024
Grayscale: Applied
Augmentations
Outputs per training example: 3
Rotation: Between -5° and +5°
Shear: ±3° Horizontal, ±0° Vertical
Brightness: Between -10% and +10%
Exposure: Between -5% and +5%
Blur: Up to 0.3px
Noise: Up to 0.5% of pixels