Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022, Proceedings, Part VIII

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Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li
Springer Nature, Sep 15, 2022 - Computers - 740 pages
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The eight-volume set LNCS 13431, 13432, 13433, 13434, 13435, 13436, 13437, and 13438 constitutes the refereed proceedings of the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, which was held in Singapore in September 2022.
The 574 revised full papers presented were carefully reviewed and selected from 1831 submissions in a double-blind review process. The papers are organized in the following topical sections:

Part I: Brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; heart and lung imaging; dermatology;

Part II: Computational (integrative) pathology; computational anatomy and physiology; ophthalmology; fetal imaging;

Part III: Breast imaging; colonoscopy; computer aided diagnosis;

Part IV: Microscopic image analysis; positron emission tomography; ultrasound imaging; video data analysis; image segmentation I;

Part V: Image segmentation II; integration of imaging with non-imaging biomarkers;

Part VI: Image registration; image reconstruction;

Part VII: Image-Guided interventions and surgery; outcome and disease prediction; surgical data science; surgical planning and simulation; machine learning – domain adaptation and generalization;

Part VIII: Machine learning – weakly-supervised learning; machine learning – model interpretation; machine learning – uncertainty; machine learning theory and methodologies.


 

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Contents

A Controllable and Simultaneous Synthesizer of Images and Annotations with Minimal Human Intervention
3
Selfsupervised Fluoroscopy Denoising
13
26em plus 1em minus 1emDiscrepancyBased Active Learning for Weakly Supervised Bleeding Segmentation in Wireless Capsule Endoscopy Images
24
Diffusion Models for Medical Anomaly Detection
35
FewShot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Metalearning
46
Aggregative Selfsupervised Feature Learning from Limited Medical Images
57
Learning Underrepresented Classes from Decentralized Partially Labeled Medical Images
67
Adversarially Robust Prototypical FewShot Segmentation with NeuralODEs
77
Graph Emotion Decoding from Visually Evoked Neural Responses
396
DualGraph Learning Convolutional Networks for Interpretable Alzheimers Disease Diagnosis
406
Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Noncontrast CT Scans
416
Learning a Semantic Representation Space for Medical Images
427
The debiasing Effect of GANBased Augmentation Methods on Skin Lesion Images
437
Accurate and Explainable ImageBased Prediction Using a Lightweight Generative Model
448
Interpretable Modeling and Reduction of Unknown Errors in Mechanistic Operators
459
Sparse Interpretation of Graph Convolutional Networks for Multimodal Diagnosis of Alzheimers Disease
469

Unified 2D and 3D Selfsupervised Pretraining via Masked Image Modeling Transformer for Ophthalmic Image Classification
88
Selfsupervised Learning of Morphological Representation for 3D EM Segments with ClusterInstance Correlations
99
Calibrating Label Distribution for ClassImbalanced BarelySupervised Knee Segmentation
109
Semisupervised Medical Image Classification with Temporal KnowledgeAware Regularization
119
Selfsupervised Pretraining of Transformers via Human Motion Forecasting for FewShot Gait Impairment Severity Estimation
130
Semisupervised Medical Image Segmentation Using CrossModel PseudoSupervision with Shape Awareness and Local Context Constraints
140
Multitask Selfsupervised Continual Learning to Pretrain Deep Models for XRay Images of Multiple Body Parts
151
A New PU Learning Framework Regularized by Global Consistency for Scribble Supervised Cardiac Segmentation
162
PrototypeAware Contrastive Learning for LongTailed Medical Image Classification
173
Combining MixedFormat Labels for AIBased Pathology Detection Pipeline in a LargeScale Knee MRI Study
183
TaskOriented Selfsupervised Learning for Anomaly Detection in Electroencephalography
193
Multiple Instance Learning with Mixed Supervision in Gleason Grading
204
An Accurate Unsupervised Liver Lesion Detection Method Using Pseudolesions
214
A Study on Cardiac MRI
224
WeaklySupervised Volumetric Image Segmentation via Scribble Annotations
234
Selflearning and OneShot Learning Based SingleSlice Annotation for 3D Medical Image Segmentation
244
Longitudinal Infant Functional Connectivity Prediction via Conditional Intensive Triplet Network
255
Leveraging Labeling Representations in UncertaintyBased Semisupervised Segmentation
265
Analyzing Brain Structural Connectivity as Continuous Random Functions
276
Learning with Context Encoding for SingleStage Cranial Bone Labeling and Landmark Localization
286
Warm Start Active Learning with Proxy Labels and Selection via Semisupervised FineTuning
297
Intervention Interaction Federated Abnormality Detection with Noisy Clients
309
Semisupervised Retinal Layer Segmentation in OCT Using Disentangled Representation with Anatomical Priors
320
PhysiologyBased Simulation of the Retinal Vasculature Enables AnnotationFree Segmentation of OCT Angiographs
330
AnomalyAware Multiple Instance Learning for Rare Anemia Disorder Classification
341
Unsupervised Domain Adaptation with Contrastive Learning for OCT Segmentation
351
Machine Learning Model Interpretation
362
An Explainable Neural Network Landscape of ReactionDiffusion Model for Cognitive Task Recognition
365
Interpretable Graph Neural Networks for ConnectomeBased Brain Disorder Analysis
375
ConsistencyPreserving Visual Question Answering in Medical Imaging
386
Machine Learning Uncertainty
479
Fusing Two Sources of Uncertainty for Semisupervised Medical Image Segmentation
480
CRISP Reliable Uncertainty Estimation for Medical Image Segmentation
492
Trusted Brain Tumor Segmentation
503
A SinglePass Uncertainty Estimation in Deep Learning for Segmentation
514
Delta Ensemble Uncertainty Estimation for a More Robust Estimation of Ejection Fraction
525
Efficient Bayesian Uncertainty Estimation for nnUNet
535
Improving Trustworthiness of AI Disease Severity Rating in Medical Imaging with Ordinal Conformal Prediction Sets
545
Machine Learning Theory and Methodologies
555
Selfsupervised Poisson Denoising from a Single Image
557
An Inclusive TaskAware Framework for Radiology Report Generation
568
Removal of Confounders via Invariant Risk Minimization for Medical Diagnosis
578
A Selfguided Framework for Radiology Report Generation
588
Counterfactual Video Generation
599
TransformerBased Semantic Query for Medical Report Generation
610
Pseudo BiasBalanced Learning for Debiased Chest XRay Classification
621
Why Patient Data Cannot Be Easily Forgotten?
632
Calibration of Medical Imaging Classification Systems with Weight Scaling
642
Online Reflective Learning for Robust Medical Image Segmentation
652
FineGrained Correlation Loss for Regression
663
Suppressing Poisoning Attacks on Federated Learning for Medical Imaging
673
The Intrinsic Manifolds of Radiological Images and Their Role in Deep Learning
684
Unlearning Scanner Bias with Distributed Data
695
Fast Unsupervised Brain Anomaly Detection and Segmentation with Diffusion Models
705
CNNs vs Traditional Model Fitting
715
Adaptive Gradient Triplet Loss with Automatic Margin Learning for Forensic Medical Image Matching
725
The Intrinsic Manifolds of Radiological Images and Their Role in Deep Learning
736
Author Index
737
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