A Universal and Efficient Method to Compute Maps from Image-Based Prediction Models

@article{Sabuncu2014AUA,
  title={A Universal and Efficient Method to Compute Maps from Image-Based Prediction Models},
  author={Mert R. Sabuncu},
  journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2014},
  volume={17 Pt 3},
  pages={353-60}
}
Discriminative supervised learning algorithms, such as Support Vector Machines, are becoming increasingly popular in biomedical image computing. One of their main uses is to construct image-based prediction models, e.g., for computer aided diagnosis or "mind reading." A major challenge in these applications is the biological interpretation of the machine learning models, which can be arbitrarily complex functions of the input features (e.g., as induced by kernel-based methods). Recent work has… CONTINUE READING
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