Advanced Collagen Fiber Orientation Analysis

Led advanced bio-imaging analysis using sophisticated machine learning techniques to predict collagen fiber orientation with high precision and innovative data augmentation methods.

Key Achievements

• Led advanced bio-imaging analysis using Fast Fourier Transform (FFT), Support Vector Regression (SVR), and CNNs, achieving 95% accuracy in collagen fiber orientation prediction
• Implemented a novel method leveraging Generative Diffusion Models in PyTorch for biological data augmentation, increasing dataset size by 10x while preserving accuracy

Technical Details

• Techniques: Fast Fourier Transform (FFT), Support Vector Regression (SVR), Convolutional Neural Networks (CNNs), Generative Diffusion Models
• Programming: PyTorch
• Performance Metrics:
  • 95% accuracy in collagen fiber orientation prediction
  • 10x dataset size increase through innovative data augmentation