BoneAgeAI Pro

Multi-modal deep learning platform for automated skeletal maturity assessment and sexual dimorphism analysis

Upload Hand Radiograph for Analysis

Drag & drop your DICOM or JPEG image here

Optimal resolution: 300-500μm pixel size, 12-bit depth

Advanced Model Architecture

Multi-Task Learning

Joint optimization of ResNet-152 and EfficientNet-B7 architectures with shared feature extraction layers.

Attention Mechanisms

Transformer-based self-attention layers focus on epiphyseal regions and trabecular patterns.

Biomarker Extraction

Automated measurement of 27 skeletal maturity indicators including ulnar styloid ossification.

Validation Metrics

MAE
0.48 years
ICC
0.98
AUC
0.94
0.96

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