Please note the program is tentative. Please note the assignment of short papers to the poster sessions is coming soon; the below program only has papers from the full paper track.

Monday, July 10

Oral session 1 - Segmentation 1 - 9:30 - 10:30am

MS-Former: Multi-Scale Self-Guided Transformer for Medical Image Segmentation
SuperMask: Generating High-resolution object masks from multi-view, unaligned low-resolution MRIs
Model Adaptive Tooth Segmentation
Learning Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations

Oral session 2 - Unsupervised/weakly supervised methods - 2:00 - 3:00pm

Joint Breast Neoplasm Detection and Subtyping using Multi-Resolution Network Trained on Large-Scale H&E Whole Slide Images with Weak Labels
Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening
Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images
DRIMET: Deep Registration-based 3D Incompressible Motion Estimation in Tagged-MRI with Application to the Tongue

Oral session 3 - Graph-based methods - 4:00 - 5:00pm

DBGDGM: Dynamic Brain Graph Deep Generative Model
Tumor Budding T-cell Graphs: Assessing the Need for Resection in pT1 Colorectal Cancer Patients
A Geometric Deep Learning Framework for Generation of Virtual Left Ventricles as Graphs
Vesselformer: Towards Complete 3D Vessel Graph Generation from Images

Posters - 11:00am - 12:00pm & 3:00pm - 4:00pm

Full paper track

A Geometric Deep Learning Framework for Generation of Virtual Left Ventricles as Graphs
DBGDGM: Dynamic Brain Graph Deep Generative Model
DRIMET: Deep Registration-based 3D Incompressible Motion Estimation in Tagged-MRI with Application to the Tongue
Generalizing Unsupervised Anomaly Detection: Towards Unbiased Pathology Screening
Joint Breast Neoplasm Detection and Subtyping using Multi-Resolution Network Trained on Large-Scale H&E Whole Slide Images with Weak Labels
Learning Clinically Acceptable Segmentation of Organs at Risk in Cervical Cancer Radiation Treatment from Clinically Available Annotations
Model Adaptive Tooth Segmentation
MS-Former: Multi-Scale Self-Guided Transformer for Medical Image Segmentation
Reproducibility of the Methods in Medical Imaging with Deep Learning.
SuperMask: Generating High-resolution object masks from multi-view, unaligned low-resolution MRIs
Tumor Budding T-cell Graphs: Assessing the Need for Resection in pT1 Colorectal Cancer Patients
Unsupervised Stain Decomposition via Inversion Regulation for Multiplex Immunohistochemistry Images
Vesselformer: Towards Complete 3D Vessel Graph Generation from Images
Interpretable histopathology-based prediction of disease relevant features in Inflammatory Bowel Disease biopsies using weakly-supervised deep learning
Denoising Diffusion Models for Memory-efficient Processing of 3D Medical Images
Reference-based MRI Reconstruction Using Texture Transformer
Domain Adaptation using Silver Standard Labels for Ki-67 Scoring in Digital Pathology A Step Closer to Widescale Deployment
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification
Video pretraining advances 3D deep learning on chest CT tasks
MEDIMP: 3D Medical Images and clinical Prompts for renal transplant representation learning
Stage Detection of Mild Cognitive Impairment: Region-dependent Graph Representation Learning on Brain Morphable Meshes
Inherently Interpretable Multi-Label Classification Using Class-Specific Counterfactuals
MultiTask Learning for accelerated-MRI Reconstruction and Segmentation of Brain Lesions in Multiple Sclerosis
Multi PILOT: Feasible Learned Multiple Acquisition Trajectories For Dynamic MRI
Few Shot Hematopoietic Cell Classification
Prior Guided 3D Medical Image Landmark Localization
Calibration techniques for node classification using graph neural networks on medical image data
ST(OR)$^2$: Spatio-Temporal Object Level Reasoning for Activity Recognition in the Operating Room
Improved multi-site Parkinson's disease classification using neuroimaging data with counterfactual inference
Radiology Reports Improve Visual Representations Learned from Radiographs
Federated Cross Learning for Medical Image Segmentation
A comparative evaluation of image-to-image translation methods for stain transfer in histopathology
OFDVDnet: A Sensor Fusion Approach for Video Denoising in Fluorescence-Guided Surgery
TransRP: Transformer-based PET/CT feature extraction incorporating clinical data for recurrence-free survival prediction in oropharyngeal cancer
SegPrompt: Using Segmentation Map as a Better Prompt to Finetune Deep Models for Kidney Stone Classification
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis
One-Class SVM on siamese neural network latent space for Unsupervised Anomaly Detection on brain MRI White Matter Hyperintensities
nnUNet meets pathology: Bridging the gap for application to whole slide images and computational biomarkers
Image2SSM: Localization-aware Deep Learning Framework for Statistical Shape Modeling Directly from Images

Short paper track

Implementation considerations for deep learning with diffusion MRI streamline tractography
Uncertainty-based Quality Controlled T1 Mapping and ECV Analysis using Bayesian Vision Transformer
Human-Guided Design to Explain Deep Learning-based Pneumothorax Classifier
End-to-End Spermatozoid Detection in Cytology WSI for Forensic Pathology Workflow
Real-Time Quantitative Ultrasound and Radar Knowledge-Based Medical Imaging
Exploring the Role of Explainability for Uncovering Bias in Deep Learning-based Medical Image Analysis
Distributed learning effectiveness in medical image analysis when trained with limited dataset
Generation of Multi-modal Brain Tumor MRIs with Disentangled Latent Diffusion Model
Data-Free One-Shot Federated Regression: An Application to Bone Age Assessment
Segmentation of seventy-one anatomical structures necessary for the evaluation of guideline-conform clinical target volumes in head and neck cancers
Automatic renal perfusion estimation on postoperative PCASL MRI based on deep learning image analysis and segmentation
A General Stitching Solution for Whole-Brain 3D Nuclei Instance Segmentation from Microscopy Images
Active learning for medical image segmentation with stochastic batches
Learning Retinal Representations from Multi-modal Imaging via Contrastive Pre-training
Combining Anomaly Detection and Supervised Learning for Medical Image Segmentation
Interactive Cell Detection in H&E-stained slides of Diffuse Gastric Cancer
PRISM: Probabilistic Interactive Segmentation for Medical Images
Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging
Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multi-Institutional Cohort Study
Overcoming Interpretability and Accuracy Trade-off in Medical Imaging
Image Entropy and Numeric Representation for MRI Semantic Segmentation
Characterizing Continual Learning Scenarios for Tumor Classification in Histopathology Images
Zeta-mixup: Richer, More Realistic Mixing of Multiple Images
Facial AU-aid hypomimia diagnosis based on GNN
Transforming Radiology Workflows: Pretraining for Automated Chest X-ray Report Generation
Automatic Contrast Phase Detection on Abdominal Computed Tomography using Clinically-Inspired Techniques
A Novel Approach for Assessment of Clonal Hematopoiesis of Indeterminate Potential Using Deep Neural Networks
Deep Learning based Automatic Segmentation of the Levator Ani Muscle from 3D Endovaginal Ultrasound Images
Radiomics using disentangled latent features from deep representation learning in soft-tissue sarcoma
Semi-supervised learning in perivascular space segmentation using MRI images
Benchmark and Boosted Segmentation on Dental Panoramic Radiographs

Tuesday, July 11

Oral session 4 - Neuroimaging - 9:00 - 10:30am

MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging
Decoding natural image stimuli from fMRI data with a surface-based convolutional network
Pre-Training Transformers for Fingerprinting to Improve Stress Prediction in fMRI
E(3) x SO(3)-Equivariant Networks for Spherical Deconvolution in Diffusion MRI
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
Data Consistent Deep Rigid MRI Motion Correction

Oral session 5 - Semi-supervised/self-supervised methods - 2:00 - 3:00pm

Vision-Language Modelling For Radiological Imaging and Reports In The Low Data Regime
Learning to Compare Longitudinal Images
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays
Self-Supervised CSF Inpainting for Improved Accuracy Validation of Cortical Surface Analyses

Oral session 6 - Synthesis - 4:00 - 5:00pm

CP2Image: Generating high-quality single-cell images using CellProfiler representations
Ultra-NeRF: Neural Radiance Fields for Ultrasound Imaging
Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors

Posters - 10:30am - 12:00pm & 3:00pm - 4:00pm

Full paper track

Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
Bi-parametric prostate MR image synthesis using pathology and sequence-conditioned stable diffusion
CP2Image: Generating high-quality single-cell images using CellProfiler representations
Data Consistent Deep Rigid MRI Motion Correction
Decoding natural image stimuli from fMRI data with a surface-based convolutional network
E(3) x SO(3)-Equivariant Networks for Spherical Deconvolution in Diffusion MRI
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors
Learning to Compare Longitudinal Images
MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging
Pre-Training Transformers for Fingerprinting to Improve Stress Prediction in fMRI
Self-Supervised CSF Inpainting for Improved Accuracy Validation of Cortical Surface Analyses
Ultra-NeRF: Neural Radiance Fields for Ultrasound Imaging
Vision-Language Modelling For Radiological Imaging and Reports In The Low Data Regime
Making Your First Choice: To Address Cold Start Problem in Medical Active Learning
Robust Detection Outcome: A Metric for Pathology Detection in Medical Images
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction
ViT-AE++: Improving Vision Transformer Autoencoder for Self-supervised Medical Image Representations
Deformable Image Registration with Geometry-informed Implicit Neural Representations
3D Medical Axial Transformer: A Lightweight Transformer Model for 3D Brain Tumor Segmentation
Joint cortical registration of geometry and function using semi-supervised learning
Semantic Segmentation of 3D Medical Images Through a Kaleidoscope: Data from the Osteoarthritis Initiative
Whole brain radiomics for clustered federated personalization in brain tumor segmentation
Incomplete learning of multi-modal connectome for brain disorder diagnosis via modal-mixup and deep supervision
Considerations for data acquisition and modeling strategies: Mitosis detection in computational pathology
Automatic 3D/2D Deformable Registration in Minimally Invasive Liver Resection using a Mesh Recovery Network
Improving Stain Invariance of CNNs for Segmentation by Fusing Channel Attention and Domain-Adversarial Training
Automatic Patient-level Diagnosis of Prostate Disease with Fused 3D MRI and Tabular Clinical Data
Reproducibility of Training Deep Learning Models for Medical Image Analysis
DBGSL: Dynamic Brain Graph Structure Learning
Alleviating tiling effect by random walk sliding window in high-resolution histological whole slide image synthesis
Evaluating the Fairness of Deep Learning Uncertainty Estimates in Medical Image Analysis
Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation
Toward Unpaired Multi-modal Medical Image Segmentation via Learning Structured Semantic Consistency
Trainable Prototype Enhanced Multiple Instance Learning for Whole Slide Image Classification
Intra- and Inter-Cellular Awareness for 3D Neuron Tracking and Segmentation in Large-Scale Connectomics
Selective experience replay compression using coresets for lifelong deep reinforcement learning in medical imaging
A deep learning method trained on synthetic data for digital breast tomosynthesis reconstruction
Estimating Uncertainty in PET Image Reconstruction via Deep Posterior Sampling
Effect of Intensity Standardization on Deep Learning for WML Segmentation in Multi-Centre FLAIR MRI

Short paper track

DD-CISENet: Dual-Domain Cross-Iteration Squeeze and Excitation Network for Accelerated MRI Reconstruction
Exploring shared memory architectures for end-to-end gigapixel deep learning
Outlier Detection for Mammograms
Contrast Invariant Feature Representations for Segmentation and Registration of Medical Images
Dilation-Erosion Methods for Radiograph Annotation in Total Knee Replacement
Neural Operator Learning for Ultrasound Tomography Inversion
Deep learning-based segmentation of rabbit fetal skull with limited and sub-optimal training labels
A Comparative Study of Unsupervised Adversarial Domain Adaptation Strategies in Multiple-instance Learning Frameworks for Digital Pathology
Unsupervised Plaque Segmentation on Whole Slide Images
GammaFocus: An image augmentation method to focus model attention for classification
Equivariant and Denoising CNNs to Decouple Intensity and Spatial Features for Motion Tracking in Fetal Brain MRI
Comp2Comp: Open-Source Body Composition Assessment on Computed Tomography
High-Fidelity Image Synthesis from Pulmonary Nodule Lesion Maps using Semantic Diffusion Model
Robust Identification of White Matter Hyperintensities in Uncontrolled Settings Using Deep Learning
Nearest Neighbor Radiomics for Self-Supervised Chest X-ray Pneumonia Identification
Zero-shot CT Field-of-view Completion with Unconditional Generative Diffusion Prior
Regularization by Denoising Diffusion Process for MRI Reconstruction
Digital Staining of Unpaired White and Blue Light Cystoscopy Videos for Bladder Cancer Detection in the Clinic
Towards Realistic Ultrasound Fetal Brain Imaging Synthesis
Assessing Deep Learning Methodologies for Automatic Segmentation of the Velopharyngeal Mechanism
On the dice loss variants and sub-patching
Anomaly Detection using Cascade Variational Autoencoder Coupled with Zero Shot Learning
Virtual staining overlay enabled combined morphological and spatial transcriptomic analysis of individual malignant B cells and local tumor microenvironments
Exploring the Optimal Operating MR Contrast for Brain Ventricle Parcellation
High-resolution 3D Maps of Left Atrial Displacements using an Unsupervised Image Registration Neural Network
Pre-training Segmentation Models for Histopathology
An end-to-end Complex-valued Neural Network approach for k-space interpolation in Parallel MRI
Improving Zero-Shot Detection of Low Prevalence Chest Pathologies using Domain Pre-trained Language Models
CSGAN: a consistent structural GAN for AS-OCT image despeckling by image translation
Synthetic Medical Image Generation Using Latent Diffusion Models and Large Language Models

Wednesday, July 12

Oral session 7 - Segmentation 2 - 9:15 - 10:00am (note the late start as the virtual poster session wraps up at 9am)

MMCFormer: Missing Modality Compensation Transformer for Brain Tumor Segmentation
Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss Function
GeoLS: Geodesic Label Smoothing for Image Segmentation

Oral session 8 - Computer-assisted diagnosis - 1:30 - 2:30pm

Sparse Activations for Interpretable Disease Grading
Simple and Efficient Confidence Score for Grading Whole Slide Images
Frozen Language Model Helps ECG Zero-Shot Learning
An end-to-end framework for diagnosing COVID-19 pneumonia via Parallel Recursive MLP module and Bi-LTSM correlation

Posters - 10:00am - 11:30am & 2:30pm - 3:30pm

Full paper track

An end-to-end framework for diagnosing COVID-19 pneumonia via Parallel Recursive MLP module and Bi-LTSM correlation
Frozen Language Model Helps ECG Zero-Shot Learning
GeoLS: Geodesic Label Smoothing for Image Segmentation
Improving Segmentation of Objects with Varying Sizes in Biomedical Images using Instance-wise and Center-of-Instance Segmentation Loss Function
Inherent Consistent Learning for Accurate Semi-supervised Medical Image Segmentation
MMCFormer: Missing Modality Compensation Transformer for Brain Tumor Segmentation
Simple and Efficient Confidence Score for Grading Whole Slide Images
Sparse Activations for Interpretable Disease Grading
Diffusion Models for Contrast Harmonization of Magnetic Resonance Images
On-the-Fly Test-time Adaptation for Medical Image Segmentation
A Robust Mean Teacher Framework for Semi-Supervised Cell Detection in Histopathology Images
Rotation-Scale Equivariant Steerable Filters
MTSR-MRI: Combined Modality Translation and Super-Resolution of Magnetic Resonance Images
Reverse Engineering Breast MRIs: Predicting Acquisition Parameters Directly from Images
Whole-slide-imaging Cancer Metastases Detection and Localization with Limited Tumorous Data
Metadata-guided Consistency Learning for High Content Images
Multimodal Image-Text Matching Improves Retrieval-based Chest X-Ray Report Generation
Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI
Spatial Correspondence between Graph Neural Network-Segmented Images
Convolutional-recurrent neural networks approximate diffusion tractography from T1-weighted MRI and associated anatomical context
Addressing Chest Radiograph Projection Bias in Deep Classification Models
Semi-supervised Learning with Contrastive and Topology Losses for Catheter Segmentation and Misplacement Prediction
Generative Adversarial Networks for Coronary CT Angiography Acquisition Protocol Correction with Explicit Attenuation Constraints
TransNetR: Transformer-based Residual Network for Polyp Segmentation with Multi-Center Out-of-Distribution Testing
SFT-KD-Recon: Learning a Student-friendly Teacher for Knowledge Distillation in Magnetic Resonance Image Reconstruction
FlexR: Few-shot Classification with Language Embeddings for Structured Reporting of Chest X-rays
Evaluating Adversarial Robustness of Low dose CT Recovery
MedSegDiff: Medical Image Segmentation with Diffusion Probabilistic Model
FUSQA: Fetal Ultrasound Segmentation Quality Assessment
Zero-Shot Self-Supervised Joint Temporal Image and Sensitivity Map Reconstruction via Linear Latent Space
Domain adaptation using optimal transport for invariant learning using histopathology datasets
A comparison of self-supervised pretraining approaches for predicting disease risk from chest radiograph images
Domain Adaptation using Silver Standard Masks for Lateral Ventricle Segmentation in FLAIR MRI

Short paper track

Segmentation of Lipid Droplets in Histological Images
High Frequency Structural MRI Signal conditioned MRA Synthesis with Denoising Diffusion probabilistic Model
Deep model-based optoacoustic image reconstruction (DeepMB)
Towards Robust Computation of Cardiothoracic Ratio from Chest X-Ray
Uncovering Structural-Functional Coupling Alterations for Neurodegenerative Diseases
A Deep-Learning Based Approach to Accelerate Groundtruth Generation for Biomarker Status Identification in Chromogenic Duplex Images
Temporal Monte Carlo Dropout for Robust Uncertainty Quantification: Application to Point-of-Care Ultrasound-guided Nerve Blocks
3D Body Composition Segmentation in Abdomen and Pelvis CT using Subdivided Labels and Random Patch
Automatic quantification of TSR as a prognostic marker for pancreatic cancer.
Local and global feature aggregation for accurate epithelial cell classification using graph attention mechanisms in histopathology images
Make nnUNets Small Again
Shape Equivariant Learning for Robust MRI Segmentation
Brain age prediction using multi-hop graph attention module(MGA) with convolutional neural network
SAM.MD: Zero-shot medical image segmentation capabilities of the Segment Anything Model
Learning Patient Rotation Using Synthetic X-ray Images from 3D CT Volumes
3D Supervised Contrastive-Learning Network for Classification of Ovarian Neoplasms
On the robustness of regressing tumor percentage as an explainable detector in histopathology whole-slide images
Uncertainty for Proximal Femur Fractures Classification
Caption generation from histopathology whole-slide images using pre-trained transformers
Mitigating Representation Shift in Unicentric Data through Logit Perturbation for Robust Histology Image Segmentation
Inter-Scale Dependency Modeling for Skin Lesion Segmentation with Transformer-based Networks
Visualizing chest X-ray dataset biases using GANs
Investigate Sex Dimorphism of Cerebral Myelination Across Lifespan by Leveraging Conditional Variational Autoencoder
FFCL: Forward-Forward Contrastive Learning for Improved Medical Image Classification
Deep Learning Regression of Cardiac Phase on Real-Time MRI
Expansion Microscopy Imaging Isotropic Restoration by Unsupervised Deep Learning
Applying spatial attention-based autoencoder learning of latent representation for unsupervised characterization of tumor microenvironment
Bias Field Correction in MRI with Hampel Noise Denoising Diffusion Probabilistic Model
Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI ‚Äî The PI-CAI Challenge
TSNet: Integrating Dental Position Prior and Symptoms for Tooth Segmentation from CBCT Images

Note that Nashville is on the UTC-5 timezone.