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Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

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Cover of 'Medical Image Computing and Computer Assisted Intervention – MICCAI 2023'

Table of Contents

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    Book Overview
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    Chapter 1 Pre-trained Diffusion Models for Plug-and-Play Medical Image Enhancement
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    Chapter 2 GRACE: A Generalized and Personalized Federated Learning Method for Medical Imaging
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    Chapter 3 Chest X-ray Image Classification: A Causal Perspective
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    Chapter 4 DRMC: A Generalist Model with Dynamic Routing for Multi-center PET Image Synthesis
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    Chapter 5 Federated Condition Generalization on Low-dose CT Reconstruction via Cross-domain Learning
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    Chapter 6 Enabling Geometry Aware Learning Through Differentiable Epipolar View Translation
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    Chapter 7 Enhance Early Diagnosis Accuracy of Alzheimer’s Disease by Elucidating Interactions Between Amyloid Cascade and Tau Propagation
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    Chapter 8 TauFlowNet : Uncovering Propagation Mechanism of Tau Aggregates by Neural Transport Equation
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    Chapter 9 Uncovering Structural-Functional Coupling Alterations for Neurodegenerative Diseases
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    Chapter 10 Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis
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    Chapter 11 Multi-Head Multi-Loss Model Calibration
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    Chapter 12 Scale Federated Learning for Label Set Mismatch in Medical Image Classification
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    Chapter 13 Cross-Modulated Few-Shot Image Generation for Colorectal Tissue Classification
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    Chapter 14 Bidirectional Mapping with Contrastive Learning on Multimodal Neuroimaging Data
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    Chapter 15 How Reliable are the Metrics Used for Assessing Reliability in Medical Imaging?
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    Chapter 16 Co-assistant Networks for Label Correction
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    Chapter 17 M3D-NCA: Robust 3D Segmentation with Built-In Quality Control
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    Chapter 18 The Role of Subgroup Separability in Group-Fair Medical Image Classification
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    Chapter 19 Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis
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    Chapter 20 SMRD: SURE-Based Robust MRI Reconstruction with Diffusion Models
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    Chapter 21 Asymmetric Contour Uncertainty Estimation for Medical Image Segmentation
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    Chapter 22 Fourier Test-Time Adaptation with Multi-level Consistency for Robust Classification
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    Chapter 23 A Model-Agnostic Framework for Universal Anomaly Detection of Multi-organ and Multi-modal Images
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    Chapter 24 DiMix: Disentangle-and-Mix Based Domain Generalizable Medical Image Segmentation
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    Chapter 25 Regular SE(3) Group Convolutions for Volumetric Medical Image Analysis
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    Chapter 26 Deep Learning-Based Anonymization of Chest Radiographs: A Utility-Preserving Measure for Patient Privacy
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    Chapter 27 Maximum Entropy on Erroneous Predictions: Improving Model Calibration for Medical Image Segmentation
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    Chapter 28 Label-Preserving Data Augmentation in Latent Space for Diabetic Retinopathy Recognition
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    Chapter 29 Assignment Theory-Augmented Neural Network for Dental Arch Labeling
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    Chapter 30 Evidence Reconciled Neural Network for Out-of-Distribution Detection in Medical Images
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    Chapter 31 Segmentation Distortion: Quantifying Segmentation Uncertainty Under Domain Shift via the Effects of Anomalous Activations
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    Chapter 32 CheXstray: A Real-Time Multi-Modal Monitoring Workflow for Medical Imaging AI
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    Chapter 33 DiffMix: Diffusion Model-Based Data Synthesis for Nuclei Segmentation and Classification in Imbalanced Pathology Image Datasets
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    Chapter 34 Fully Bayesian VIB-DeepSSM
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    Chapter 35 Performance Metrics for Probabilistic Ordinal Classifiers
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    Chapter 36 Boundary-Weighted Logit Consistency Improves Calibration of Segmentation Networks
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    Chapter 37 Fine-Tuning Network in Federated Learning for Personalized Skin Diagnosis
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    Chapter 38 Deployment of Image Analysis Algorithms Under Prevalence Shifts
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    Chapter 39 Understanding Silent Failures in Medical Image Classification
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    Chapter 40 Towards Frugal Unsupervised Detection of Subtle Abnormalities in Medical Imaging
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    Chapter 41 A Privacy-Preserving Walk in the Latent Space of Generative Models for Medical Applications
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    Chapter 42 Deep Learning-Based Air Trapping Quantification Using Paired Inspiratory-Expiratory Ultra-low Dose CT
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    Chapter 43 Data AUDIT: Identifying A ttribute U tility- and  D etectability- I nduced Bias in  T ask Models
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    Chapter 45 Anatomical-Aware Point-Voxel Network for Couinaud Segmentation in Liver CT
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    Chapter 46 Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels
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    Chapter 47 SwinMM: Masked Multi-view with Swin Transformers for 3D Medical Image Segmentation
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    Chapter 48 Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos
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    Chapter 49 UniSeg: A Prompt-Driven Universal Segmentation Model as Well as A Strong Representation Learner
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    Chapter 50 Joint Dense-Point Representation for Contour-Aware Graph Segmentation
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    Chapter 51 Structure-Preserving Instance Segmentation via Skeleton-Aware Distance Transform
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    Chapter 52 Deep Mutual Distillation for Semi-supervised Medical Image Segmentation
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    Chapter 53 HENet: Hierarchical Enhancement Network for Pulmonary Vessel Segmentation in Non-contrast CT Images
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    Chapter 54 Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts
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    Chapter 55 Trust Your Neighbours: Penalty-Based Constraints for Model Calibration
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    Chapter 56 DHC: Dual-Debiased Heterogeneous Co-training Framework for Class-Imbalanced Semi-supervised Medical Image Segmentation
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    Chapter 57 FocalUNETR: A Focal Transformer for Boundary-Aware Prostate Segmentation Using CT Images
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    Chapter 58 Unpaired Cross-Modal Interaction Learning for COVID-19 Segmentation on Limited CT Images
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    Chapter 59 3D Medical Image Segmentation with Sparse Annotation via Cross-Teaching Between 3D and 2D Networks
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    Chapter 60 Minimal-Supervised Medical Image Segmentation via Vector Quantization Memory
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    Chapter 61 Guiding the Guidance: A Comparative Analysis of User Guidance Signals for Interactive Segmentation of Volumetric Images
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    Chapter 62 MultiTalent: A Multi-dataset Approach to Medical Image Segmentation
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    Chapter 63 Uncertainty and Shape-Aware Continual Test-Time Adaptation for Cross-Domain Segmentation of Medical Images
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    Chapter 64 CorSegRec: A Topology-Preserving Scheme for Extracting Fully-Connected Coronary Arteries from CT Angiography
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    Chapter 65 Scale-Aware Test-Time Click Adaptation for Pulmonary Nodule and Mass Segmentation
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    Chapter 66 ACC-UNet: A Completely Convolutional UNet Model for the 2020s
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    Chapter 67 Automatic Segmentation of Internal Tooth Structure from CBCT Images Using Hierarchical Deep Learning
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    Chapter 68 Robust T-Loss for Medical Image Segmentation
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    Chapter 69 Self-adaptive Adversarial Training for Robust Medical Segmentation
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    Chapter 70 Laplacian-Former: Overcoming the Limitations of Vision Transformers in Local Texture Detection
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    Chapter 71 DAST: Differentiable Architecture Search with Transformer for 3D Medical Image Segmentation
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    Chapter 72 WeakPolyp: You only Look Bounding Box for Polyp Segmentation
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Title
Medical Image Computing and Computer Assisted Intervention – MICCAI 2023
Published by
Springer Nature Switzerland, October 2023
DOI 10.1007/978-3-031-43898-1
ISBNs
978-3-03-143897-4, 978-3-03-143898-1
Editors

Greenspan, Hayit, Madabhushi, Anant, Mousavi, Parvin, Salcudean, Septimiu, Duncan, James, Syeda-Mahmood, Tanveer, Taylor, Russell

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