Patch-Based Techniques in Medical Imaging

Chapter 1 4D Multi-atlas Label Fusion Using Longitudinal Images

Chapter 2 Brain Image Labeling Using Multi-atlas Guided 3D Fully Convolutional Networks

Chapter 3 Whole Brain Parcellation with Pathology: Validation on Ventriculomegaly Patients

Chapter 5 On the Role of Patch Spaces in Patch-Based Label Fusion

Chapter 6 Learning a Sparse Database for Patch-Based Medical Image Segmentation

Chapter 7 Accurate and High Throughput Cell Segmentation Method for Mouse Brain Nuclei Using Cascaded Convolutional Neural Network

Chapter 8 Learning-Based Estimation of Functional Correlation Tensors in White Matter for Early Diagnosis of Mild Cognitive Impairment

Chapter 9 Early Prediction of Alzheimer’s Disease with Non-local Patch-Based Longitudinal Descriptors

Chapter 10 Adaptive Fusion of Texture-Based Grading: Application to Alzheimer’s Disease Detection

Chapter 11 Micro-CT Guided 3D Reconstruction of Histological Images

Chapter 12 A Neural Regression Framework for Low-Dose Coronary CT Angiography (CCTA) Denoising

Chapter 13 A Dictionary Learning-Based Fast Imaging Method for Ultrasound Elastography

Chapter 14 Breast Tumor Detection in Ultrasound Images Using Deep Learning

Chapter 15 Modeling the Intra-class Variability for Liver Lesion Detection Using a Multi-class Patch-Based CNN

Chapter 16 Multiple Sclerosis Lesion Segmentation Using Joint Label Fusion

Chapter 17 Deep Multimodal Case–Based Retrieval for Large Histopathology Datasets

Chapter 18 Sparse Representation Using Block Decomposition for Characterization of Imaging Patterns