Nassir Navab

Latest

• Digital staining of white blood cells with confidence estimation
• ROAM: Random layer mixup for semi-supervised learning in medical images
• Semi-Supervised Federated Peer Learning for Skin Lesion Classification
• TriMix: Virtual embeddings and self-consistency for self-supervised learning
• Unsupervised Cross-Domain Feature Extraction for Single Blood Cell Image Classification
• What can we learn about a generated image corrupting its latent representation?
• Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study
• Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study
• Butterfly-Net: Spatial-Temporal Architecture For Medical Image Segmentation
• FedPerl: Semi-Supervised Peer Learning for Skin Lesion Classification
• Fourier Transform of Percoll Gradients Boosts CNN Classification of Hereditary Hemolytic Anemias
• Microaneurysms segmentation and diabetic retinopathy detection by learning discriminative representations
• Modeling Healthy Anatomy with Artificial Intelligence for Unsupervised Anomaly Detection in Brain MRI
• Sickle Cell Disease Severity Prediction from Percoll Gradient Images using Graph Convolutional Networks
• Multi-task multi-domain learning for digital staining and classification of leukocytes
• An Uncertainty-Driven GCN Refinement Strategy for Organ Segmentation
• 6D Camera Relocalization in Ambiguous Scenes via Continuous Multimodal Inference
• Fairness by Learning Orthogonal Disentangled Representations
• Uncertainty-based graph convolutional networks for organ segmentation refinement
• Seamless Virtual Whole Slide Image Synthesis and Validation Using Perceptual Embedding Consistency
• A learning without forgetting approach to incorporate artifact knowledge in polyp localization tasks
• An Uncertainty-Driven GCN Refinement Strategy for Organ Segmentation
• Attention Based Multiple Instance Learning for Classification of Blood Cell Disorders
• Bayesian Skip-Autoencoders for Unsupervised Hyperintense Anomaly Detection in High Resolution Brain Mri
• GANs for medical image analysis
• Image-to-Images Translation for Multi-Task Organ Segmentation and Bone Suppression in Chest X-Ray Radiography
• Inverse Distance Aggregation for Federated Learning with Non-IID Data
• On the Fairness of Privacy-Preserving Representations in Medical Applications
• Polyp-artifact relationship analysis using graph inductive learned representations
• Precise proximal femur fracture classification for interactive training and surgical planning.
• Retinal Layer Segmentation Reformulated as OCT Language Processing
• ROAM: Random Layer Mixup for Semi-Supervised Learning in Medical Imaging
• Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI
• SteGANomaly: Inhibiting CycleGAN Steganography for Unsupervised Anomaly Detection in Brain MRI
• Understanding the effects of artifacts on automated polyp detection and incorporating that knowledge via learning without forgetting
• Adaptive image-feature learning for disease classification using inductive graph networks
• Adversarial Networks for Camera Pose Regression and Refinement
• Focal loss for artefact detection in medical endoscopy
• Fusing unsupervised and supervised deep learning for white matter lesion segmentation
• Graph Convolution Based Attention Model for Personalized Disease Prediction
• InceptionGCN: receptive field aware graph convolutional network for disease prediction
• Investigation of Focal Loss in Deep Learning Models For Femur Fractures Classification
• Learn to estimate labels uncertainty for quality assurance
• Learn to Segment Organs with a Few Bounding Boxes
• Learning interpretable disentangled representations using adversarial vaes
• Learning Interpretable Features via Adversarially Robust Optimization
• Learning-based x-ray image denoising utilizing model-based image simulations
• Multi-scale Microaneurysms Segmentation Using Embedding Triplet Loss
• Perceptual Embedding Consistency for Seamless Reconstruction of Tilewise Style Transfer
• Preliminary results of DSA denoising based on a weighted low-rank approach using an advanced neurovascular replication system
• Self-attention equipped graph convolutions for disease prediction
• Semi-Supervised Few-Shot Learning with Prototypical Random Walks
• Staingan: Stain style transfer for digital histological images
• Towards an Interactive and Interpretable CAD System to Support Proximal Femur Fracture Classification
• Virtualization of tissue staining in digital pathology using an unsupervised deep learning approach
• A photon recycling approach to the denoising of ultra-low dose X-ray sequences
• Deep autoencoding models for unsupervised anomaly segmentation in brain MR images
• Domain and geometry agnostic CNNs for left atrium segmentation in 3D ultrasound
• GANs for medical image analysis
• Generalizing multistain immunohistochemistry tissue segmentation using one-shot color deconvolution deep neural networks
• Generating highly realistic images of skin lesions with GANs
• Multiple device segmentation for fluoroscopic imaging using multi-task learning
• Scene coordinate and correspondence learning for image-based localization
• Weakly-supervised localization and classification of proximal femur fractures
• When regression meets manifold learning for object recognition and pose estimation
• X-ray Depthmaps: Revealing the Hidden Structures
• Automatic classification of proximal femur fractures based on attention models
• Semi-supervised deep learning for fully convolutional networks
• X-ray in-depth decomposition: Revealing the latent structures
• X-Ray PoseNet: 6 DoF pose estimation for mobile X-Ray devices
• Aggnet: deep learning from crowds for mitosis detection in breast cancer histology images
• Cathnets: detection and single-view depth prediction of catheter electrodes
• Playsourcing: a novel concept for knowledge creation in biomedical research
• Single-view X-ray depth recovery: toward a novel concept for image-guided interventions
• Structure-preserving color normalization and sparse stain separation for histological images
• Gradient projection for regularized cryo-electron tomographic reconstruction
• Structure-preserved color normalization for histological images