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Machine Learning in Medical Imaging

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Cover of 'Machine Learning in Medical Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Structural MRI Harmonization via Disentangled Latent Energy-Based Style Translation
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    Chapter 2 Cross-Domain Iterative Network for Simultaneous Denoising, Limited-Angle Reconstruction, and Attenuation Correction of Cardiac SPECT
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    Chapter 3 Arbitrary Reduction of MRI Inter-slice Spacing Using Hierarchical Feature Conditional Diffusion
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    Chapter 4 Reconstruction of 3D Fetal Brain MRI from 2D Cross-Sectional Acquisitions Using Unsupervised Learning Network
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    Chapter 5 Robust Unsupervised Super-Resolution of Infant MRI via Dual-Modal Deep Image Prior
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    Chapter 6 SR4ZCT: Self-supervised Through-Plane Resolution Enhancement for CT Images with Arbitrary Resolution and Overlap
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    Chapter 7 unORANIC: Unsupervised Orthogonalization of Anatomy and Image-Characteristic Features
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    Chapter 8 An Investigation of Different Deep Learning Pipelines for GABA-Edited MRS Reconstruction
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    Chapter 9 Towards Abdominal 3-D Scene Rendering from Laparoscopy Surgical Videos Using NeRFs
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    Chapter 10 Brain MRI to PET Synthesis and Amyloid Estimation in Alzheimer’s Disease via 3D Multimodal Contrastive GAN
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    Chapter 11 Accelerated MRI Reconstruction via Dynamic Deformable Alignment Based Transformer
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    Chapter 12 Deformable Cross-Attention Transformer for Medical Image Registration
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    Chapter 13 Deformable Medical Image Registration Under Distribution Shifts with Neural Instance Optimization
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    Chapter 14 Implicitly Solved Regularization for Learning-Based Image Registration
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    Chapter 15 BHSD: A 3D Multi-class Brain Hemorrhage Segmentation Dataset
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    Chapter 16 Contrastive Learning-Based Breast Tumor Segmentation in DCE-MRI
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    Chapter 17 FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation
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    Chapter 18 Mammo-SAM: Adapting Foundation Segment Anything Model for Automatic Breast Mass Segmentation in Whole Mammograms
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    Chapter 19 Consistent and Accurate Segmentation for Serial Infant Brain MR Images with Registration Assistance
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    Chapter 20 Unifying and Personalizing Weakly-Supervised Federated Medical Image Segmentation via Adaptive Representation and Aggregation
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    Chapter 21 Unlocking Fine-Grained Details with Wavelet-Based High-Frequency Enhancement in Transformers
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    Chapter 22 Prostate Segmentation Using Multiparametric and Multiplanar Magnetic Resonance Images
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    Chapter 23 SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation
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    Chapter 24 Automated Coarse-to-Fine Segmentation of Thoracic Duct Using Anatomy Priors and Topology-Guided Curved Planar Reformation
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    Chapter 25 Leveraging Self-attention Mechanism in Vision Transformers for Unsupervised Segmentation of Optical Coherence Microscopy White Matter Images
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    Chapter 26 PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation
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    Chapter 27 A Super Token Vision Transformer and CNN Parallel Branch Network for mCNV Lesion Segmentation in OCT Images
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    Chapter 28 Boundary-RL: Reinforcement Learning for Weakly-Supervised Prostate Segmentation in TRUS Images
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    Chapter 29 A Domain-Free Semi-supervised Method for Myocardium Segmentation in 2D Echocardiography Sequences
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    Chapter 30 Self-training with Domain-Mixed Data for Few-Shot Domain Adaptation in Medical Image Segmentation Tasks
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    Chapter 31 Bridging the Task Barriers: Online Knowledge Distillation Across Tasks for Semi-supervised Mediastinal Segmentation in CT
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    Chapter 32 RelationalUNet for Image Segmentation
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    Chapter 33 Interpretability-Guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data
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    Chapter 34 Improving Automated Prostate Cancer Detection and Classification Accuracy with Multi-scale Cancer Information
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    Chapter 35 Skin Lesion Segmentation Improved by Transformer-Based Networks with Inter-scale Dependency Modeling
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    Chapter 36 MagNET: Modality-Agnostic Network for Brain Tumor Segmentation and Characterization with Missing Modalities
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    Chapter 37 Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model
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    Chapter 38 IA-GCN: Interpretable Attention Based Graph Convolutional Network for Disease Prediction
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    Chapter 39 Multi-modal Adapter for Medical Vision-and-Language Learning
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    Chapter 40 Vector Quantized Multi-modal Guidance for Alzheimer’s Disease Diagnosis Based on Feature Imputation
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    Chapter 41 Finding-Aware Anatomical Tokens for Chest X-Ray Automated Reporting
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    Chapter 42 Dual-Stream Model with Brain Metrics and Images for MRI-Based Fetal Brain Age Estimation
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    Chapter 43 PECon: Contrastive Pretraining to Enhance Feature Alignment Between CT and EHR Data for Improved Pulmonary Embolism Diagnosis
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    Chapter 44 Exploring the Transfer Learning Capabilities of CLIP in Domain Generalization for Diabetic Retinopathy
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    Chapter 45 More from Less: Self-supervised Knowledge Distillation for Routine Histopathology Data
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    Chapter 46 Tailoring Large Language Models to Radiology: A Preliminary Approach to LLM Adaptation for a Highly Specialized Domain
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Title
Machine Learning in Medical Imaging
Published by
Springer Nature Switzerland, November 2023
DOI 10.1007/978-3-031-45673-2
ISBNs
978-3-03-145672-5, 978-3-03-145673-2
Editors

Cao, Xiaohuan, Xu, Xuanang, Rekik, Islem, Cui, Zhiming, Ouyang, Xi

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