Medical Image Computing and Computer Assisted Intervention – MICCAI 2023

Table of Contents

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   Book Overview
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   Chapter 1 Category-Level Regularized Unlabeled-to-Labeled Learning for Semi-supervised Prostate Segmentation with Multi-site Unlabeled Data
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   Chapter 2 Devil is in Channels: Contrastive Single Domain Generalization for Medical Image Segmentation
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   Chapter 3 Transformer-Based Annotation Bias-Aware Medical Image Segmentation
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   Chapter 4 Uncertainty-Informed Mutual Learning for Joint Medical Image Classification and Segmentation
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   Chapter 5 A General Stitching Solution for Whole-Brain 3D Nuclei Instance Segmentation from Microscopy Images
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   Chapter 6 Adult-Like Phase and Multi-scale Assistance for Isointense Infant Brain Tissue Segmentation
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   Chapter 7 Robust Segmentation via Topology Violation Detection and Feature Synthesis
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   Chapter 8 GL-Fusion: Global-Local Fusion Network for Multi-view Echocardiogram Video Segmentation
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    Chapter 9 Treasure in Distribution: A Domain Randomization Based Multi-source Domain Generalization for 2D Medical Image Segmentation
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    Chapter 10 Diffusion Kinetic Model for Breast Cancer Segmentation in Incomplete DCE-MRI
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    Chapter 11 CAS-Net: Cross-View Aligned Segmentation by Graph Representation of Knees
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    Chapter 12 One-Shot Traumatic Brain Segmentation with Adversarial Training and Uncertainty Rectification
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    Chapter 13 MI-SegNet: Mutual Information-Based US Segmentation for Unseen Domain Generalization
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    Chapter 14 M-GenSeg: Domain Adaptation for Target Modality Tumor Segmentation with Annotation-Efficient Supervision
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    Chapter 15 Factor Space and Spectrum for Medical Hyperspectral Image Segmentation
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    Chapter 16 RBGNet: Reliable Boundary-Guided Segmentation of Choroidal Neovascularization
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    Chapter 17 QCResUNet: Joint Subject-Level and Voxel-Level Prediction of Segmentation Quality
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    Chapter 18 Consistency-Guided Meta-learning for Bootstrapping Semi-supervised Medical Image Segmentation
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    Chapter 19 ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast
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    Chapter 20 TransNuSeg: A Lightweight Multi-task Transformer for Nuclei Segmentation
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    Chapter 21 Learnable Cross-modal Knowledge Distillation for Multi-modal Learning with Missing Modality
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    Chapter 22 EchoGLAD: Hierarchical Graph Neural Networks for Left Ventricle Landmark Detection on Echocardiograms
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    Chapter 23 Class-Aware Feature Alignment for Domain Adaptative Mitochondria Segmentation
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    Chapter 24 A Sheaf Theoretic Perspective for Robust Prostate Segmentation
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    Chapter 25 Semi-supervised Domain Adaptive Medical Image Segmentation Through Consistency Regularized Disentangled Contrastive Learning
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    Chapter 26 Few-Shot Medical Image Segmentation via a Region-Enhanced Prototypical Transformer
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    Chapter 27 Morphology-Inspired Unsupervised Gland Segmentation via Selective Semantic Grouping
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    Chapter 28 Boundary Difference over Union Loss for Medical Image Segmentation
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    Chapter 29 Do We Really Need that Skip-Connection? Understanding Its Interplay with Task Complexity
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    Chapter 30 Conditional Temporal Attention Networks for Neonatal Cortical Surface Reconstruction
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    Chapter 31 Elongated Physiological Structure Segmentation via Spatial and Scale Uncertainty-Aware Network
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    Chapter 32 EoFormer: Edge-Oriented Transformer for Brain Tumor Segmentation
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    Chapter 33 Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network
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    Chapter 34 Shape-Aware 3D Small Vessel Segmentation with Local Contrast Guided Attention
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    Chapter 35 HartleyMHA: Self-attention in Frequency Domain for Resolution-Robust and Parameter-Efficient 3D Image Segmentation
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    Chapter 36 EdgeMixup: Embarrassingly Simple Data Alteration to Improve Lyme Disease Lesion Segmentation and Diagnosis Fairness
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    Chapter 37 Learning Ontology-Based Hierarchical Structural Relationship for Whole Brain Segmentation
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    Chapter 38 Fine-Grained Hand Bone Segmentation via Adaptive Multi-dimensional Convolutional Network and Anatomy-Constraint Loss
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    Chapter 39 MedNeXt: Transformer-Driven Scaling of ConvNets for Medical Image Segmentation
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    Chapter 40 SwinUNETR-V2: Stronger Swin Transformers with Stagewise Convolutions for 3D Medical Image Segmentation
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    Chapter 41 Medical Boundary Diffusion Model for Skin Lesion Segmentation
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    Chapter 42 Instructive Feature Enhancement for Dichotomous Medical Image Segmentation
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    Chapter 43 MDViT: Multi-domain Vision Transformer for Small Medical Image Segmentation Datasets
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    Chapter 44 Semi-supervised Class Imbalanced Deep Learning for Cardiac MRI Segmentation
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    Chapter 45 Collaborative Modality Generation and Tissue Segmentation for Early-Developing Macaque Brain MR Images
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    Chapter 46 EGE-UNet: An Efficient Group Enhanced UNet for Skin Lesion Segmentation
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    Chapter 47 BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation
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    Chapter 48 DBTrans: A Dual-Branch Vision Transformer for Multi-Modal Brain Tumor Segmentation
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    Chapter 49 Memory Replay for Continual Medical Image Segmentation Through Atypical Sample Selection
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    Chapter 50 Structure-Decoupled Adaptive Part Alignment Network for Domain Adaptive Mitochondria Segmentation
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    Chapter 51 Deep Probability Contour Framework for Tumour Segmentation and Dose Painting in PET Images
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    Chapter 52 Annotator Consensus Prediction for Medical Image Segmentation with Diffusion Models
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    Chapter 53 Anti-adversarial Consistency Regularization for Data Augmentation: Applications to Robust Medical Image Segmentation
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    Chapter 54 SimPLe: Similarity-Aware Propagation Learning for Weakly-Supervised Breast Cancer Segmentation in DCE-MRI
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    Chapter 55 Multi-shot Prototype Contrastive Learning and Semantic Reasoning for Medical Image Segmentation
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    Chapter 56 Self-supervised Learning via Inter-modal Reconstruction and Feature Projection Networks for Label-Efficient 3D-to-2D Segmentation
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    Chapter 57 RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection
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    Chapter 58 Certification of Deep Learning Models for Medical Image Segmentation
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    Chapter 59 Diffusion Transformer U-Net for Medical Image Segmentation
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    Chapter 60 Scaling up 3D Kernels with Bayesian Frequency Re-parameterization for Medical Image Segmentation
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    Chapter 61 ConvFormer: Plug-and-Play CNN-Style Transformers for Improving Medical Image Segmentation
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    Chapter 62 Edge-Aware Multi-task Network for Integrating Quantification Segmentation and Uncertainty Prediction of Liver Tumor on Multi-modality Non-contrast MRI
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    Chapter 63 UPCoL: Uncertainty-Informed Prototype Consistency Learning for Semi-supervised Medical Image Segmentation
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    Chapter 64 A2FSeg: Adaptive Multi-modal Fusion Network for Medical Image Segmentation
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    Chapter 65 Learning Reliability of Multi-modality Medical Images for Tumor Segmentation via Evidence-Identified Denoising Diffusion Probabilistic Models
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    Chapter 66 H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
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    Chapter 67 Evolutionary Normalization Optimization Boosts Semantic Segmentation Network Performance
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    Chapter 68 DOMINO ++ : Domain-Aware Loss Regularization for Deep Learning Generalizability
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    Chapter 69 Ariadne’s Thread: Using Text Prompts to Improve Segmentation of Infected Areas from Chest X-ray Images
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    Chapter 70 NISF: Neural Implicit Segmentation Functions
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    Chapter 71 Multimodal CT and MR Segmentation of Head and Neck Organs-at-Risk
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    Chapter 72 Conditional Diffusion Models for Weakly Supervised Medical Image Segmentation
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    Chapter 73 From Sparse to Precise: A Practical Editing Approach for Intracardiac Echocardiography Segmentation
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    Chapter 74 Ischemic Stroke Segmentation from a Cross-Domain Representation in Multimodal Diffusion Studies
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    Chapter 75 Pre-operative Survival Prediction of Diffuse Glioma Patients with Joint Tumor Subtyping