Better Generalization of White Matter Tract Segmentation to Arbitrary Datasets with Scaled Residual Bootstrap

Computer Science

• Noise-to-Signal Ratio 100%
• Deep Neural Network 66%
• Training Model 66%
• Segmentation Approach 66%
• Experimental Result 33%
• segmentation accuracy 33%
• Residual Signal 33%
• Segmentation Model 33%
• Signal Representation 33%
• Linear Representation 33%

Mathematics

• Residuals 100%
• Bootstrapping 100%
• Magnetic Resonance Imaging 71%
• Noise Ratio 42%
• Deep Neural Network 28%
• Test Data 28%
• Training Data 14%