Interpretability of Machine Intelligence in Medical Image Computing and Multimodal Learning for Clinical Decision Support

Chapter 1 Testing the Robustness of Attribution Methods for Convolutional Neural Networks in MRI-Based Alzheimer’s Disease Classification

Chapter 2 UBS: A Dimension-Agnostic Metric for Concept Vector Interpretability Applied to Radiomics

Chapter 3 Generation of Multimodal Justification Using Visual Word Constraint Model for Explainable Computer-Aided Diagnosis

Chapter 4 Incorporating Task-Specific Structural Knowledge into CNNs for Brain Midline Shift Detection

Chapter 5 Guideline-Based Additive Explanation for Computer-Aided Diagnosis of Lung Nodules

Chapter 6 Deep Neural Network or Dermatologist?

Chapter 7 Towards Interpretability of Segmentation Networks by Analyzing DeepDreams

Chapter 9 Deep Learning Based Multi-modal Registration for Retinal Imaging

Chapter 10 Automated Enriched Medical Concept Generation for Chest X-ray Images