Deep Learning-Based Spectral Unmixing for Optoacoustic Imaging of Tissue Oxygen Saturation

Keyphrases

• Deep Learning Methods 100%
• Spectral Unmixing 100%
• Photoacoustic Imaging 100%
• Eigenvalue Spectrum 100%
• Multispectral Optoacoustic Tomography 100%
• Tissue Oxygen Saturation 100%
• Inverse Problem 40%
• Neural Network Architecture 20%
• Optimization Problem 20%
• Deep Learning 20%
• Biomedical Applications 20%
• Nonconvex 20%
• Spatial Features 20%
• Label-free 20%
• Convolutional Layer 20%
• Spectral Features 20%
• Recurrent Layer 20%
• Spectral Changes 20%
• Optoacoustic 20%
• Wavelength Dependence 20%
• Mouse in Vivo 20%
• Small Animal 20%
• Subepidermal 20%
• Oxygen Saturation 20%
• Tissue Depth 20%
• Light Attenuation 20%
• Light Fluence 20%
• Blood Phantom 20%
• Experimental Dataset 20%
• Label-free Imaging 20%
• Animal-mouse 20%

Engineering

• Deep Learning 100%
• Learning Approach 50%
• Optimisation Problem 50%
• Ground Truth 50%
• Biomedical Application 50%
• Simulated Data 50%
• Recurrent 50%
• Neural Network Architecture 50%
• Dependent Attenuation 50%
• Spatial Feature 50%
• Spectral Feature 50%
• Convolutional Layer 50%
• Optimality 50%
• Input Spectrum 50%

Physics

• Tomography 100%
• Deep Learning 100%
• Label-Free 40%
• Fluence 40%
• Neural Network 20%