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

Short program Note that Nashville is on the UTC-5 timezone.