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 — 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.