A curated list of awesome MICCAI 2024 accepted papers with available code implementations.
- Classification
- Data Analysis
- Detection
- Image Enhancement
- Image Generation
- Motion Analysis
- Natural Language Processing
- Prediction
- Quality Assessment
- Reconstruction
- Registration
- Segmentation
- Miscellaneous
Aο¬nity Learning Based Brain Function Representation for Disease Diagnosis | Task: Diagnosis | π Paper | π» Code
BrainSCK: Brain Structure and Cognition Alignment for Diagnosing Brain Disorders | Task: Classification | π Paper | π» Code
BrainWaveNet: Wavelet-Based Transformer for Autism Spectrum Disorder Diagnosis | Task: Diagnosis | π Paper | π» Code
Customized Relationship Graph Neural Network for Brain Disorder Identification | Task: Classification | π Paper | π» Code
DTCA: Dual-Branch Transformer with Cross-Attention for EEG and Eye Movement Data Fusion | Task: Classification | π Paper | π» Code
Exploring Spatio-temporal Interpretable Dynamic Brain Function with Transformer | Task: Classification | π Paper | π» Code
Representing Functional Connectivity with Structural Detour | Task: Cognitive state classification and early diagnosis of Alzheimerβs disease | π Paper | π» Code
Quality-Aware Fuzzy Min-Max Neural Networks for Dynamic Brain Network Analysis | Task: Classification | π Paper | π» Code
Self-guided Knowledge-Injected GNN for Alzheimer's Diseases | Task: Classification | π Paper
Graph Neural Networks with Domain-Generalizable Explainability for Brain Disorder Diagnosis | Task: Classification | π Paper | π» Code
Multi-level Contrastive Learning Method for Disease Diagnosis | Task: Classification | π Paper | π» Code
CP-CLIP for Zero-Shot Medical Image Analysis | Task: Zero-shot classification | π Paper | π» Code
Cross-Modality Cardiac Insight Transfer | Task: classification, regression | π Paper | π» Code
Decoding the Visual Attention of Pathologists | Task: Classification | π Paper
DiRecT: Diagnosis and Reconstruction Transformer for Mandibular Deformity | Task: Diagnosis of mandibular deformity | π Paper | π» Code
Boosting Medical Image Analysis via Motion-Informed Generative Videos | Task: Classification | π Paper | π» Code
Genomics-Guided Representation Learning for Pathologic Pan-Cancer Tumor Microenvironment Subtype Prediction | Task: classification | π Paper | π» Code
MoRA: LoRA Guided Multi-modal Disease Diagnosis | Task: Disease diagnosis | π Paper | π» Code
Prior Activation Map Guided Cervical OCT Image Classification | Task: Classification | π Paper | π» Code
The MRI Scanner as a Diagnostic | Task: classification | π Paper | π» Code
New Dataset and Baseline Model for Rectal Cancer Risk Assessment | Task: Classification | π Paper | π» Code
Analyzing Cross-Population Domain Shift in Chest X-Ray Image Classification | Task: Classification | π Paper | π» Code
FedMRL: Data Heterogeneity Aware Federated Multi-agent Deep Reinforcement Learning for Medical Imaging | Task: Classification | π Paper | π» Code
Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound | Task: lesion detection, classification | π Paper | π» Code
Neural Cellular Automata for White Blood Cell Image Classification | Task: Classification | π Paper | π» Code
PASSION for Dermatology | Task: Classification | π Paper | π» Code
Multilevel Causality Learning for Multi-label Gastric Atrophy Diagnosis | Task: Multi-label Classification | π Paper | π» Code
Patch-Slide Discriminative Joint Learning | Task: Classification | π Paper | π» Code
A Domain Adaption Approach for EEG-Based Automated Seizure Classification | Task: classification | π Paper | π» Code
Region-Based Approach to Diabetic Retinopathy Classification | Task: classification | π Paper | π» Code
ACLNet: A Deep Learning Model for ACL Rupture Classification | Task: Classification | π Paper
A Scanning Laser Ophthalmoscopy Image Database and Trustworthy Retinal Disease Detection Method | Task: classification | π Paper | π» Code
Adapting Pre-trained Generative Model to Medical Image for Data Augmentation | Task: classification, data augmentation | π Paper | π» Code
Anatomy-Aware Gating Network for Explainable Alzheimerβs Disease Diagnosis | Task: Classification | π Paper | π» Code
Automated Spinal MRI Labelling | Task: Classification | π Paper | π» Code
Active Label Refinement for Robust Medical Image Classification | Task: Classification | π Paper | π» Code
Cardiovascular Disease Detection from Multi-view Chest X-Rays with BI-Mamba | Task: Classification | π Paper | π» Code
Adaptive Curriculum Query Strategy for Active Learning | Task: classification | π Paper | π» Code
Advancing Brain Imaging Analysis | Task: Classification | π Paper | π» Code
Correlation-Adaptive Multi-view CEUS Fusion for Liver Cancer Diagnosis | Task: Diagnosis | π Paper | π» Code
Assessing Risk of Stealing Proprietary Models | Task: Classification | π Paper | π» Code
Dual-Modality Watershed Fusion Network | Task: Classification | π Paper | π» Code
Graph Vision Mamba for Pediatric Bone Age Assessment | Task: classification | π Paper | π» Code
Enhancing Gait Video Analysis in Neurodegenerative Diseases by Knowledge Augmentation in Vision Language Model | Task: Classification | π Paper | π» Code
Gait Patterns as Biomarkers | Task: Classification | π Paper | π» Code
Disease-Informed Adaptation of Vision-Language Models | Task: Binary classification, multi-class classification | π Paper | π» Code
Improved Learning from Imbalanced Multi-label Datasets of Inflamed Joints | Task: Classification | π Paper | π» Code
Improved Esophageal Varices Assessment | Task: Classification | π Paper | π» Code
Iterative Online Image Synthesis for Imbalanced Classification | Task: classification | π Paper | π» Code
Incorporating Clinical Guidelines Through Adapting Multi-modal Large Language Model for Prostate Cancer | Task: Classification | π Paper | π» Code
Feature Fusion Based on Mutual-Cross-Attention Mechanism for EEG Emotion Recognition | Task: classification | π Paper | π» Code
Generating Progressive Images from Pathological Transitions Via Diffusion Model | Task: Image generation, Classification | π Paper | π» Code
MMFusion: Multi-modality Model for Lymph Node Metastasis Diagnosis in Esophageal Cancer | Task: Diagnosis | π Paper | π» Code
Multi-order Simplex-Based Graph Neural Network for Brain Network Analysis | Task: Classification | π Paper | π» Code
Location Embedding Based Pairwise Distance Learning for Diagnosis of Urinary Stones | Task: Classification | π Paper | π» Code
Loose Lesion Location Self-supervision Enhanced Colorectal Cancer Diagnosis | Task: Classification | π Paper | π» Code
Poisson Ordinal Network for Gleason Group Estimation | Task: Ordinal classification | π» Code
RDD-Net | Task: classification | π Paper | π» Code
Semantics-Aware Attention Guidance for Diagnosing WSIs | Task: Classification | π Paper | π» Code
Open-Set Semi-supervised Medical Image Classification | Task: Classification | π Paper | π» Code
ScaPT: Scaffold Prompt Tuning for Efficient Adaptation of fMRI Pre-trained Model | Task: prediction, neurodegenerative disease diagnosis/prognosis | π Paper | π» Code
Semi-supervised Medical Image Classification | Task: Classification | π Paper | π» Code
Reprogramming Distillation for Medical Foundation Models | Task: classification | π Paper | π» Code
Self-supervised Contrastive Graph Views for Learning Neuron-Level Circuit Network | Task: Neuron classification, Connection prediction | π Paper | π» Code
Towards Multi-modality Fusion | Task: classification | π Paper | π» Code
Self-supervised Learning with Adaptive Graph Structure and Function Representation for Cross-Dataset Brain Disorder Diagnosis | Task: Diagnosis | π Paper | π» Code
VDPF: Enhancing DVT Staging Performance Using a Global-Local Feature Fusion Network | Task: Classification | π Paper | π» Code
Semi-supervised Lymph Node Metastasis Classification | Task: Classification | π Paper
Spatio-Temporal Contrast Network for Data-Efficient Learning of Coronary Artery Disease in Coronary CT Angiography | Task: Diagnosis | π Paper | π» Code
Tail-Enhanced Representation Learning | Task: Multi-label classification | π Paper | π» Code
TARDRL:Task-Aware Reconstruction | Task: Disease diagnosis | π Paper | π» Code
Subject-Adaptive Transfer Learning Using Resting State EEG Signals | Task: classification | π Paper | π» Code
Topological Cycle Graph Attention Network for Brain Functional Connectivity | Task: Classification | π Paper | π» Code
Graph-SLC for AD Diagnosis | Task: Diagnosis | π Paper | π» Code
A Framework for Assessing Joint Human-AI Systems | Task: Classification | π Paper | π» Code
Privacy Protection in MRI Scans Using 3D Masked Autoencoders | Task: de-identification | π Paper | π» Code
Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis | Task: Classification | π Paper | π» Code
AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis | Task: classification | π Paper | π» Code
Aligning Human Knowledge with Visual Concepts | Task: classification | π Paper | π» Code
BiasPruner : Debiased Continual Learning for Medical Image Classiο¬cation | Task: classification | π Paper | π» Code
CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning | Task: Classification | π Paper | π» Code
Confidence Matters: Enhancing Medical Image Classification | Task: Classification | π Paper | π» Code
Controllable Counterfactual Generation | Task: classification | π Paper | π» Code
Data-Algorithm-Architecture Co-Optimization for Fair Neural Networks | Task: Classification | π Paper | π» Code
Debiased Noise Editing on Foundation Models for Fair Medical Image Classification | Task: Classification | π Paper | π» Code
Effective Confidence Estimation for Image Classification | Task: Misclassification Detection, Confidence Estimation | π Paper | π» Code
Diο¬Explainer | Task: Classification | π Paper | π» Code
Disentangled Attention Graph Neural Network for Alzheimerβs Disease Diagnosis | Task: Diagnosis | π Paper | π» Code
Federated Client Unlearning in Medical Imaging | Task: Classification | π Paper | π» Code
Enhancing Federated Learning Performance Fairness | Task: classification | π Paper
Fairness of Neural Collapse in Medical Image Classification | Task: classification | π Paper | π» Code
Evidential Concept Embedding Models | Task: diagnosis | π Paper | π» Code
FairQuantize | Task: Classification | π Paper | π» Code
Explainable Vertebral Fracture Analysis | Task: classification | π Paper | π» Code
Feature Selection Gates with Gradient Routing | Task: Classification | π Paper | π» Code
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging | Task: classification | π Paper | π» Code
FedMLP | Task: Multi-label classification | π Paper | π» Code
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations | Task: Classification | π Paper | π» Code
Image Distillation for Safe Data Sharing | Task: Classification | π Paper | π» Code
IMG-GCN: Interpretable Modularity-Guided Structure-Function Interactions Learning for Brain Cognition and Disorder Analysis | Task: Classification | π Paper | π» Code
Interpretable Phenotypic Profiling of 3D Cellular Morphodynamics | Task: Classification | π Paper | π» Code
LS+: Informed Label Smoothing for Improving Calibration in Medical Image Classification | Task: Classification | π Paper | π» Code
Modeling and Understanding Uncertainty in Medical Image Classification | Task: classification | π Paper | π» Code
SiFT: A Serial Framework with Textual Guidance for Federated Learning | Task: classification | π Paper | π» Code
Stealing Knowledge from Pre-trained Language Models | Task: Classification | π Paper | π» Code
Tackling Data Hheterogeneity in Federated Learning | Task: classification | π Paper | π» Code
Proto-BagNets for Interpretability | Task: Classification | π Paper | π» Code
Uncertainty-Aware Multi-view Learning for Prostate Cancer Grading with DWI | Task: Classification | π Paper | π» Code
XTranPrune: eXplainability-Aware Transformer Pruning for Bias Mitigation in Dermatological Disease Classification | Task: Classification | π Paper | π» Code
SkinCON: Consensus for Skin Cancer Sub-typing with DRAPS | Task: Classification | π Paper | π» Code
Coarse-Grained Mask Regularization for Microvascular Obstruction Identification | Task: identification | π Paper | π» Code
BPaCo: Balanced Parametric Contrastive Learning for Long-Tailed Medical Image Classification | Task: classification | π Paper | π» Code
Neural Cellular Diffusion for High-Resolution Image Synthesis | Task: Image Synthesis, Classification | π Paper | π» Code
MPMNet: Modal Prior Mutual-Support Network for AMD Classification | Task: Classification | π Paper
Hierarchical Multiple Instance Learning for COPD Grading | Task: Classification | π Paper | π» Code
Multi-disease Detection in Retinal Images | Task: Classification | π Paper | π» Code
COVID19 to Pneumonia: Multi Region Lung Severity Classiο¬cation Using CNN | Task: Classification | π Paper | π» Code
Gaze-Directed Vision GNN for Mitigating Shortcut Learning in Medical Image | Task: classification | π Paper | π» Code
Diο¬3Dformer: Leveraging Slice Sequence Diο¬usion for Enhanced 3D CT Classiο¬cation | Task: classification | π Paper | π» Code
Algorithmic Fairness in Lesion Classification | Task: classification | π Paper | π» Code
EchoFM | Task: classification | π Paper | π» Code
Multimodal Variational Autoencoder for Cardiac Hemodynamics Instability Detection | Task: Classification | π Paper | π» Code
Robustly Optimized Network for Fatty Liver Detection | Task: Classification | π Paper | π» Code
Fair and Accurate Skin Disease Image Classification | Task: Classification | π Paper | π» Code
Insight: A Multi-modal Diagnostic Pipeline Using LLMs | Task: Diagnosis | π Paper | π» Code
Adjusting CNN Model for Diagnosing Gout from MSK Ultrasound | Task: Classification | π Paper | π» Code
Enhancing Model Generalisability Through Sampling | Task: Classification | π Paper | π» Code
CLIP-DR: Textual Knowledge-Guided Diabetic Retinopathy Grading | Task: classification | π Paper | π» Code
Reliable Multi-view Learning with Conformal Prediction for Aortic Stenosis Classification | Task: classification | π Paper | π» Code
HDilemma: Open-Source Hausdorff Distance Implementations | Task: Performance evaluation | π Paper | π» Code
Surface-Based and Shape-Informed U-Fiber Atlasing | Task: connectivity analysis | π Paper | π» Code
NeuroConText | Task: Meta-analysis | π Paper | π» Code
SpeChrOmics: A Biomarker Characterization Framework for Medical Hyperspectral Imaging | Task: Biomarker characterization | π Paper | [π» Code](https://(link)
Backdoor in Medical Image Analysis | Task: Security analysis | π Paper | π» Code
BGF-YOLO: Enhanced YOLOv8 with Multiscale Attentional Feature Fusion for Brain Tumor Detection | Task: Detection | π Paper | π» Code
Cross-Slice Attention and Evidential Critical Loss for Uncertainty-Aware Prostate Cancer Detection | Task: Detection | π Paper | π» Code
Multi-Domain Leukemia Dataset for WBC Detection | Task: Detection | π Paper | π» Code
Analyzing Adjacent B-Scans to Localize Sickle Cell Retinopathy In OCTs | Task: Object detection | π Paper | π» Code
FD-SOS | Task: detection | π Paper | π» Code
Hybrid CNN-Transformer Feature Pyramid Network for Granular AAC Detection | Task: detection | π Paper | π» Code
Cephalometric Landmark Detection Across Ages | Task: Landmark Detection | π Paper | π» Code
Binary Noise for Binary Tasks | Task: Unsupervised Anomaly Detection | π Paper | π» Code
D-MASTER: Mask Annealed Transformer for Unsupervised Domain Adaptation in Breast Cancer Detection | Task: Unsupervised Domain Adaptation for breast cancer detection | π Paper | π» Code
Ensembled Cold-Diο¬usion Restorations for Anomaly Detection | Task: Unsupervised Anomaly Detection | π Paper | π» Code
Epileptic Seizure Detection in SEEG Signals Using a Uniο¬ed Multi-Scale Temporal-Spatial-Spectral Transformer Model | Task: detection | π Paper | π» Code
Language-Enhanced Local-Global Aggregation Network for Multi-organ Trauma Detection | Task: Multi-organ trauma detection | π Paper | π» Code
FM-OSD: Foundation Model-Enabled One-Shot Detection | Task: Anatomical Landmark Detection | π Paper | π» Code
Leveraging the Mahalanobis Distance for Unsupervised Brain MRI Anomaly Detection | Task: Anomaly Detection | π Paper | π» Code
MediCLIP: Adapting CLIP for Few-Shot Medical Image Anomaly Detection | Task: anomaly detection | π Paper | π» Code
Slice-Consistent Lymph Nodes Detection Transformer in CT Scans | Task: Detection | π Paper | π» Code
Spatial-Aware Attention Generative Adversarial Network for Semi-supervised Anomaly Detection in Medical Image | Task: Anomaly Detection | π Paper | π» Code
Autoencoders for Medical Anomaly Detection | Task: Anomaly Detection | π Paper | π» Code
Deeper Insight Into Face Detection in Neonatal Wards | Task: Detection | π Paper | π» Code
Vessel-Aware Aneurysm Detection Using Multi-scale Deformable 3D Attention | Task: detection | π Paper | π» Code
Topological SLAM in Colonoscopies | Task: Simultaneous Localization and Mapping (SLAM) | π Paper | π» Code
WSSADN: A Weakly Supervised Spherical Age-Disentanglement Network for Detecting Developmental Disorders with Structural MRI | Task: disease detection | π Paper | π» Code
Physical-Priors-Guided Aortic Dissection Detection Using NCE-CT | Task: Detection | π Paper | π» Code
Anatomical Positional Embeddings | Task: Representation learning, few-shot localization | π Paper | π» Code
Out-of-Distribution Detection in Digital Pathology | Task: out-of-distribution detection | π Paper | π» Code
DeepRepViz: Identifying Potential Confounders | Task: confounder detection | π Paper | π» Code
Detecting Noisy Labels with Repeated Cross-Validations | Task: Label noise detection | π Paper | π» Code
Clinically Relevant Multi-view Cues for Breast Cancer Detection from Mammograms | Task: Detection | π Paper | π» Code
Representation Learning with a Transformer-Based Model for Localized Chest X-Ray Disease Detection | Task: Disease Detection and Progression Monitoring | π Paper | π» Code
Geometric Transformation Uncertainty for Improving 3D Fetal Brain Pose Prediction | Task: Localization | π Paper | π» Code
Confidence-Guided Semi-supervised Learning for Lesion Localization in X-Ray Images | Task: Localization | π Paper | π» Code
Position-Guided Prompt Learning for Anomaly Detection in Chest X-Rays | Task: Anomaly Detection | π Paper | π» Code
MMBCD: Multimodal Breast Cancer Detection | Task: Detection | π Paper | π» Code
A Clinical-Oriented Lightweight Network for High-Resolution Medical Image Enhancement | Task: Image Enhancement | π Paper | π» Code
Cross-Modal Diffusion Modelling for Super-Resolved Spatial Transcriptomics | Task: Super-resolution | π Paper | π» Code
Enhanced-QuickDWI: Achieving Equivalent Clinical Quality by Denoising Sub-sampled Diffusion-Weighted Imaging Data | Task: Image Denoising | π Paper | π» Code
Self-supervised Denoising and Bulk Motion Artifact Removal of 3D Optical Coherence Tomography Angiography | Task: denoising and artifact removal | π Paper | π» Code
7T MRI Synthesization from 3T Acquisitions | Task: Image Enhancement | π Paper | π» Code
Baikal: Unpaired Denoising of Fluorescence Microscopy Images Using Diffusion Models | Task: Denoising | π Paper | π» Code
CAPTURE-GAN | Task: Artifact removal | π Paper | π» Code
Deform-Mamba Network for MRI Super-Resolution | Task: Super-Resolution | π Paper | π» Code
EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy | Task: Image enhancement | π Paper | π» Code
PET Image Denoising Based on 3D Denoising Model | Task: Image Denoising | π Paper | π» Code
Reference-Free Axial Super-Resolution of 3D Microscopy Images Using Implicit Neural Representation with a 2D Diffusion Prior | Task: super-resolution | π Paper | π» Code
Simultaneous Tri-Modal Medical Image Fusion and Super-Resolution | Task: fusion, super-resolution | π Paper | π» Code
SinoSynth for Generalizable CBCT Image Enhancement | Task: Image Enhancement | π Paper | π» Code
Volumetric Conditional Score-Based Residual Diffusion Model for PET/MR Denoising | Task: denoising | π Paper | π» Code
WIA-LD2ND: Wavelet-Based Image Alignment for Self-supervised Low-Dose CT Denoising | Task: Denoising | π Paper | π» Code
Zero-Shot Low-Field MRI Enhancement | Task: Enhancement | π Paper
Multi-frequency and Smoke Attention-Aware Learning Based Diffusion Model | Task: Image enhancement | π Paper | π» Code
Myocardial Scar Enhancement with Local Diffusion | Task: Image Enhancement | π Paper | π» Code
Masked Residual Diο¬usion Probabilistic Model | Task: image synthesis | π Paper | π» Code
Advancing Text-Driven Chest X-Ray Generation with Policy-Based Reinforcement Learning | Task: Image Generation | π Paper | π» Code
Structural Entities Extraction and Patient Indications Incorporation for Chest X-Ray Report Generation | Task: report generation | π Paper | π» Code
Super-Field MRI Synthesis for Infant Brains | Task: Image synthesis | π Paper | π» Code
RadiomicsFill-Mammo: Synthetic Mammogram Mass Manipulation with Radiomics Features | Task: Synthetic Tumor Generation | π Paper | π» Code
3D Vessel Graph Generation Using Denoising Diffusion | Task: Graph generation | π Paper | π» Code
Continually Tuning a Large Language Model for Multi-domain Radiology Report Generation | Task: Report generation | π Paper | π» Code
Energy-Based Controllable Radiology Report Generation | Task: Report Generation | π Paper | π» Code
GMoD: Graph-Driven Momentum Distillation | Task: report generation | π Paper | π» Code
KARGEN | Task: Report Generation | π Paper | π» Code
Non-adversarial Learning: Vector-Quantized Latent Space for Multi-sequence MRI | Task: synthesis | π Paper | π» Code
Textual Inversion and Self-supervised Reο¬nement for Radiology Report Generation | Task: Radiology report generation | π Paper | π» Code
Towards Learning Contrast Kinetics with Multi-condition Latent Diffusion Models | Task: Image synthesis | π Paper | π» Code
Anatomically-Controllable Medical Image Generation | Task: Image Generation | π Paper | π» Code
CA VM: Conditional Autoregressive Vision Model for Contrast-Enhanced Brain Tumor MRI Synthesis | Task: synthesis | π Paper | π» Code
Contrast Representation Learning for MRI Synthesis | Task: Image synthesis | π Paper | π» Code
EchoNet-Synthetic | Task: Synthetic data generation | π Paper | π» Code
HeartBeat | Task: Video Synthesis | π Paper | π» Code
Memory-Efficient High-Resolution OCT Volume Synthesis | Task: synthesis | π Paper | π» Code
Structural Attention: Rethinking Transformer for Unpaired Medical Image Synthesis | Task: unpaired medical image synthesis | π Paper | π» Code
Tagged-to-Cine MRI Sequence Synthesis | Task: synthesis | π Paper
Evaluating the Quality of Brain MRI Generators | Task: generation | π Paper | π» Code
Mitigating Attribute Ampliο¬cation in Counterfactual Image Generation | Task: counterfactual image generation | π Paper | π» Code
Groupwise Deformable Registration of Diffusion Tensor Cardiovascular Magnetic Resonance | Task: Motion Correction | π Paper | π» Code
CardioSpectrum: Comprehensive Myocardium Motion Analysis with 3D Deep Learning and Geometric Insights | Task: Myocardial motion analysis | π Paper | π» Code
Trexplorer: Recurrent DETR for Tree Centerline Tracking | Task: centerline tracking | π Paper | π» Code
Differentiable Score-Based Likelihoods: Learning CT Motion Compensation from Clean Images | Task: Motion Compensation | π Paper | π» Code
IM-MoCo: Self-supervised MRI Motion Correction | Task: motion correction | π Paper | π» Code
Physics-Informed Deep Learning for Motion-Corrected Reconstruction of Quantitative Brain MRI | Task: Motion Correction | π Paper | π» Code
Resolving Variable Respiratory Motion From Unsorted 4D Computed Tomography | Task: motion model optimization | π Paper | π» Code
MRScore | Task: Radiology report evaluation | π Paper | π» Code
LLMsβ Tuning Methods in Medical Multimodal Domain | Task: Visual Question Answering | π Paper | π» Code
DermaVQA | Task: Question Answering | π Paper | π» Code
BIMCV-R | Task: text-image retrieval | π Paper | π» Code
Coarse-to-Fine Grained Representations in Contrastive Learning for Medical VQA | Task: Visual Question Answering | π Paper | π» Code
MMQL: Multi-Question Learning | Task: Medical Visual Question Answering (Med-VQA) | π Paper | π» Code
Region-Specific Retrieval Augmentation | Task: Visual Question Answering (VQA) | π Paper | π» Code
Spot the Diο¬erence: Diο¬erence Visual Question Answering with Residual Alignment | Task: visual question answering | π Paper | π» Code
Conditional Score-Based Diffusion Model for Cortical Thickness Trajectory Prediction | Task: Prediction | π Paper | π» Code
In Vivo Deep Learning Estimation of Nanoparticle Diffusion | Task: Estimation of diffusion coefficients | π Paper | π» Code
MARVEL: MR Fingerprinting with micRoVascular Estimates Using BiLSTMs | Task: Parameter estimation | π Paper | π» Code
MGDR | Task: Prediction | π Paper
SOM2LM: Self-Organized Multi-Modal Longitudinal Maps | Task: cross-modality prediction, joint-modality prediction | π Paper | π» Code
TADM: Temporally-Aware Diffusion Model for Neurodegenerative Progression | Task: Prediction of neurodegenerative progression | π Paper | π» Code
tDCS Digital Twins Using Deep Learning | Task: Estimation | π Paper | π» Code
Disease Progression Prediction Incorporating Genotype-Environment Interactions | Task: Prediction | π Paper | π» Code
DRIM: Learning Disentangled Representations from Incomplete Multimodal Healthcare Data | Task: Prognosis prediction | π Paper | π» Code
LLM-Guided Multi-modal Multiple Instance Learning for 5-Year Overall Survival Prediction of Lung Cancer | Task: Survival Prediction | π Paper | π» Code
Predicting 3D Bone Locations | Task: prediction | π Paper | π» Code
PG-MLIF: Multimodal Low-Rank Interaction Fusion Framework for Cancer Prognosis | Task: Prognosis prediction | π Paper | π» Code
Prediction of Disease-Related Femur Shape Changes Using Geometric Encoding and Clinical Context on a Hip Disease CT Database | Task: Prediction of Disease-Related Femur Shape Changes | π Paper | π» Code
Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs | Task: Prediction of disease progression and treatment response | π Paper | π» Code
Vestibular Schwannoma Growth Prediction | Task: growth prediction | π Paper | π» Code
3D Spine Shape Estimation from Single 2D DXA | Task: Shape estimation | π Paper | π» Code
ccRCC Metastasis Prediction via Exploring High-Order Correlations on Multiple WSIs | Task: Metastasis prediction | π Paper | π» Code
Ensemble of Prior-guided Expert Graph Models for Survival Prediction in Digital Pathology | Task: Survival Prediction | π Paper | π» Code
Forecasting Disease Progression with Parallel Hyperplanes | Task: Disease progression forecasting | π Paper | π» Code
Hierarchical Graph Learning with Small-World Brain Connectomes | Task: Cognitive prediction | π Paper | π» Code
HoG-Net: Hierarchical Multi-organ Graph Network for Cancer Prediction | Task: recurrence prediction | π Paper | π» Code
HuLP: Human-in-the-Loop for Prognosis | Task: Prognosis | π Paper | π» Code
F2TNet: FMRI to T1w MRI Knowledge Transfer Network for Brain Multi-phenotype Prediction | Task: Prediction | π Paper | π» Code
LOMIA-T: A Transformer-Based Framework for Predicting Treatment Response | Task: prediction | π Paper | π» Code
Longitudinal Mammogram Risk Prediction | Task: Risk Prediction | π Paper | π» Code
Longitudinally Consistent Individual Prediction | Task: Prediction | π Paper | π» Code
M2Fusion | Task: prediction of pathological complete response | π Paper | π» Code
Latent Spaces Enable Transformer-Based Dose Prediction | Task: Dose prediction | π Paper | π» Code
Multimodal Learning for Embryo Viability Prediction | Task: viability prediction | π Paper | π» Code
ORCGT: Ollivier-Ricci Curvature-Based Graph Model for Lung STAS Prediction | Task: Prediction | π Paper | π» Code
Physics Informed Neural Networks for Estimation of Tissue Properties from Multi-echo MRI | Task: parameter estimation | π Paper | π» Code
SurvRNC: Learning Ordered Representations for Survival Prediction Using Rank-N-Contrast | Task: Survival Prediction | π Paper | π» Code
TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing | Task: mPAP estimation | π Paper | π» Code
Structure-Preserving Image Translation for Depth Estimation in Colonoscopy | Task: Depth estimation | π Paper | π» Code
Spatiotemporal Representation Learning for Short and Long Medical Image Time Series | Task: Prognosis, Estimation | π Paper | π» Code
AutoSkull: Learning-Based Skull Estimation for Automated Pipelines | Task: Skull shape estimation | π Paper | π» Code
Estimating Neural Orientation Distribution Fields on High Resolution Diο¬usion MRI Scans | Task: Estimation of Orientation Distribution Function (ODF) | π Paper | π» Code
Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Breast Cancer Events | Task: Risk prediction, Time-to-event prediction | π Paper | π» Code
Refining IOL Power Calculation Using Cross-Layer Attention and ECA | Task: prediction | π Paper | π» Code
Generalized Robust Fundus Photography-Based Vision Loss Estimation for High Myopia | Task: Estimation of visual field | π Paper | π» Code
Double-Tier Attention Based Multi-label Learning Network | Task: Biomarker prediction | π Paper | π» Code
Context-Aware Gaze Estimation | Task: Estimation | π Paper | π» Code
Improving Therapy Response Prediction | Task: Prediction | π Paper | π» Code
HUP-3D: 3D Multi-view Synthetic Dataset for Hand-Ultrasound-Probe Pose Estimation | Task: pose estimation | π Paper | π» Code
Temporal Neighboring Multi-modal Transformer with Missingness-Aware Prompt for Hepatocellular Carcinoma Prediction | Task: prediction | π Paper | π» Code
Unsupervised Ultrasound Image Quality Assessment | Task: Image Quality Assessment | π Paper | π» Code
HAMIL-QA: Hierarchical Approach | Task: Quality Assessment | π Paper | π» Code
Conditional Diο¬usion Model for Versatile Temporal Inpainting in 4D Cerebral CT Perfusion Imaging | Task: Temporal Inpainting | π Paper | π» Code
Cortical Surface Reconstruction from 2D MRI with Segmentation-Constrained Super-Resolution and Representation Learning | Task: Surface Reconstruction | π Paper | π» Code
PX2Tooth: Reconstructing the 3D Point Cloud Teeth from a Single Panoramic X-Ray | Task: 3D reconstruction | π Paper | π» Code
LGS: A Light-Weight 4D Gaussian Splatting for Eο¬cient Surgical Scene Reconstruction | Task: 3D Reconstruction | π Paper | π» Code
Self-supervised 3D Skeleton Completion | Task: skeleton completion | π Paper | π» Code
Weakly Supervised Learning of Cortical Surface Reconstruction | Task: Cortical Surface Reconstruction | π Paper | π» Code
3DDX Bone Surface Reconstruction from Single Radiograph | Task: Reconstruction | π Paper | π» Code
3DGR-CAR: Coronary Artery Reconstruction from Ultra-sparse 2D X-Ray Views | Task: Reconstruction | π Paper | π» Code
3DPX: Progressive 2D-to-3D Oral Image Reconstruction | Task: reconstruction | π Paper | π» Code
All-In-One Medical Image Restoration | Task: All-In-One Medical Image Restoration | π» Code
Accelerated Multi-contrast MRI | Task: Reconstruction | π Paper | π» Code
Evaluation of State-of-the-Art Projectors with Noise and Nonlinearity | Task: Image Reconstruction | π Paper | π» Code
APS-USCT | Task: Image Reconstruction | π Paper | π» Code
Blind Proximal Diο¬usion Model for Joint Image and Sensitivity Estimation in Parallel MRI | Task: reconstruction | π Paper
Convolutional Implicit Neural Representation of Pathology Whole-Slide Images | Task: Image Reconstruction | π Paper | π» Code
Cycle-Consistent Learning for Fetal Cortical Surface Reconstruction | Task: Cortical surface reconstruction | π Paper
Dynamic Hybrid Unrolled Multi-scale Network for Accelerated MRI Reconstruction | Task: Reconstruction | π Paper | π» Code
Explanation-Driven Cyclic Learning for Brain MRI Reconstruction | Task: Reconstruction | π Paper
Fine-Grained Context and Multi-modal Alignment for Freehand 3D Ultrasound Reconstruction | Task: 3D freehand ultrasound reconstruction | π Paper | π» Code
Free-SurGS: SfM-Free 3D Gaussian Splatting for Surgical Scene Reconstruction | Task: 3D Reconstruction | π Paper | π» Code
k-t Self-consistency Diffusion: A Physics-Informed Model for Dynamic MR Imaging | Task: Reconstruction | π Paper | π» Code
Learning 3D Gaussians for Sparse CBCT Reconstruction | Task: Reconstruction | π Paper | π» Code
LiverUSRecon | Task: 3D reconstruction and volumetry | π Paper | π» Code
Noise Level Adaptive Diffusion Model | Task: Reconstruction | π Paper | π» Code
Instabilities of Unsupervised Denoising Diffusion Models in MRI | Task: Image Reconstruction | π Paper | π» Code
Parameter Efficient Fine Tuning for Multi-scanner PET to PET Reconstruction | Task: Reconstruction | π Paper | π» Code
Region Attention Transformer | Task: Image Restoration | π Paper | π» Code
Self-supervised k-Space Regularization for Motion-Resolved Abdominal MRI Using Neural Implicit k-Space Representations | Task: Reconstruction | π Paper | π» Code
Bone Shape Reconstruction from Biplanar X-Rays | Task: Bone Reconstruction | π Paper | π» Code
SRE-CNN: A Spatiotemporal Rotation-Equivariant CNN for Cardiac Cine MR Imaging | Task: Image reconstruction | π Paper | π» Code
TeethDreamer: 3D Teeth Reconstruction | Task: 3D reconstruction | π Paper | π» Code
Two Projections Suffice for Cerebral Vascular Reconstruction | Task: 3D Reconstruction | π Paper | π» Code
VolumeNeRF: CT Volume Reconstruction from a Single Projection View | Task: Reconstruction | π Paper | π» Code
Hallucination Index: An Image Quality Metric for Generative Reconstruction Models | Task: Image reconstruction | π Paper | π» Code
Interpretable Representation Learning of Cardiac MRI via Attribute Regularization | Task: Reconstruction | π Paper | π» Code
Algebraic Sphere Surface Fitting for Accurate and Efficient Mesh Reconstruction from Cine CMR Images | Task: Mesh reconstruction | π Paper | π» Code
Deep-Learning-Based Groupwise Registration for Motion Correction of Cardiac T1Mapping | Task: Registration | π Paper | π» Code
Diο¬useReg: Denoising Diο¬usion Model for Deformation Fields in Image Registration | Task: Image Registration | π Paper | π» Code
DINO-Reg: General Purpose Image Encoder for Training-Free Deformable Registration | Task: Image Registration | π Paper | π» Code
Epicardium Prompt-Guided Real-Time Cardiac Ultrasound Frame-to-Volume Registration | Task: Registration | π Paper | π» Code
Heteroscedastic Uncertainty Estimation Framework for Unsupervised Registration | Task: image registration | π Paper | π» Code
Hierarchical Symmetric Normalization Registration Using Deformation-Inverse Network | Task: registration | π Paper | π» Code
On-the-Fly Guidance Training for Medical Image Registration | Task: Registration | π Paper | π» Code
Online Learning in Motion Modeling | Task: image registration, motion modeling | π Paper | π» Code
PULPo | Task: Registration | π Paper | π» Code
uniGradICON: A Foundation Model for Medical Image Registration | Task: Medical Image Registration | π Paper | π» Code
WiNet: Wavelet-Based Incremental Learning for Efficient Medical Image Registration | Task: Image Registration | π Paper | π» Code
MemWarp: Discontinuity-Preserving Cardiac Registration | Task: Deformable image registration | π Paper | π» Code
3D-SAutoMed: Automatic Segment | Task: Segmentation | π Paper | π» Code
Adaptive Hypergraph Neural Network for Image Segmentation | Task: segmentation | π Paper | π» Code
Mixture-of-Experts Model for Missing Modality Segmentation | Task: Segmentation | π Paper | π» Code
Weakly-Supervised Multi-lesion Segmentation Framework | Task: Segmentation | π Paper | π» Code
Adaptive Smooth Activation Function for Improved Organ Segmentation and Disease Diagnosis | Task: Segmentation, Classification | π Paper | π» Code
UWF-SLO Vessel Segmentation with Source-Free Active Domain Adaptation | Task: Segmentation | π Paper | π» Code
Uncertainty-Guided Tiered Self-training Framework for Active Source-Free Domain Adaptation | Task: Segmentation | π Paper | π» Code
AMONuSeg: Histological Dataset for African Multi-organ Nuclei Segmentation | Task: Segmentation | π Paper | π» Code
ASPS: Augmented Segment Anything Model for Polyp Segmentation | Task: segmentation | π Paper | π» Code
Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation | Task: Segmentation | π Paper | π» Code
BGDiffSeg | Task: segmentation | π Paper | π» Code
Causal Intervention for Brain Tumor Segmentation | Task: Segmentation | π Paper | π» Code
CINA: Conditional Implicit Neural Atlas | Task: Atlas generation, Segmentation, Age Prediction | π Paper | π» Code
Conditional Diο¬usion Model for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Deformation-Aware Segmentation Network | Task: Segmentation | π Paper | π» Code
DES-SAM: Distillation-Enhanced Semantic SAM for Segmentation with Box Annotation | Task: Segmentation | π Paper | π» Code
Domain Adaptation of Echocardiography Segmentation Via Reinforcement Learning | Task: segmentation | π Paper | π» Code
DPMNet: Dual-Path MLP-Based Network for Aneurysm Image Segmentation | Task: Segmentation | π Paper | π» Code
EM-Net: Efficient Channel and Frequency Learning with Mamba for 3D Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Efficient In-Context Medical Segmentation | Task: Segmentation | π Paper | π» Code
Few-Shot 3D Volumetric Segmentation with Multi-surrogate Fusion | Task: segmentation | π Paper | π» Code
Fuzzy Attention-Based Border Rendering Network for Lung Segmentation | Task: Segmentation | π Paper | π» Code
Hemodynamic-Driven Multi-prototypes Learning for One-Shot Segmentation | Task: segmentation | π Paper | π» Code
HyperSpace: Hypernetworks for Spacing-Adaptive Image Segmentation | Task: segmentation | π Paper | π» Code
HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion Segmentation | Task: Segmentation | π Paper | π» Code
Learning to Segment Multiple Organs from Multimodal Partially Labeled Datasets | Task: segmentation | π Paper | π» Code
Osteocytes Teach SR-MicroCT Bone Lacunae Segmentation | Task: Segmentation | π Paper | π» Code
LB-UNet: A Lightweight Boundary-Assisted UNet for Skin Lesion Segmentation | Task: Skin lesion segmentation | π Paper | π» Code
LM-UNet: Whole-Body PET-CT Lesion Segmentation with Dual-Modality-Based Annotations | Task: Segmentation | π Paper | π» Code
LIDIA: Precise Liver Tumor Diagnosis | Task: Diagnosis, Segmentation | π Paper
MAdapter: Image and Language Medical Segmentation | Task: Segmentation | π Paper | π» Code
Uncertainty-Guided Cardiac Cine MRI Segmentation | Task: Segmentation | π Paper | π» Code
MetaUNETR | Task: Segmentation | π Paper | π» Code
Medical Image Segmentation via Single-Source Domain Generalization with Random Amplitude Spectrum Synthesis | Task: Segmentation | π Paper | π» Code
Multi-Scale Region-Aware Implicit Neural Network | Task: Segmentation | π Paper | π» Code
ModelMix: A New Model-Mixup Strategy for Few-Scribble Cardiac Segmentation | Task: Segmentation | π Paper | π» Code
Perspective+ Unet: Enhancing Segmentation with Bi-Path Fusion and Efficient Non-Local Attention | Task: Segmentation | π Paper | π» Code
Progressive Growing of Patch Size | Task: Segmentation | π Paper | π» Code
nnU-Net Revisited | Task: Segmentation | π Paper | π» Code
Rethinking Abdominal Organ Segmentation | Task: Segmentation | π Paper | π» Code
SAM Guided Enhanced Nuclei Segmentation | Task: Segmentation | π Paper | π» Code
SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Anatomically-Guided Segmentation of Cerebral Microbleeds | Task: Segmentation | π Paper | π» Code
SANGRE: a Shallow Attention Network Guided by Resolution Expansion for MR Image Segmentation | Task: Segmentation | π Paper | π» Code
Self-paced Sample Selection for Barely-Supervised Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
SiNGR: Brain Tumor Segmentation | Task: Segmentation | π Paper | π» Code
Simple Yet Effective Prior-Aware Pseudo-labeling | Task: Segmentation | π Paper | π» Code
Swin-UMamba | Task: Segmentation | π Paper | π» Code
TinyU-Net | Task: Segmentation | π Paper | π» Code
Tri-Plane Mamba: Efficiently Adapting Segment Anything Model for 3D Medical Images | Task: segmentation | π Paper | π» Code
Efficient Cortical Surface Parcellation | Task: Segmentation | π Paper | π» Code
Soft-Labeled Contrastive Learning for Cardiac Image Segmentation | Task: Segmentation | π Paper | π» Code
Visual-Textual Matching Attention | Task: Segmentation | π Paper | π» Code
VLSM-Adapter: Finetuning Vision-Language Segmentation Efficiently with Lightweight Blocks | Task: Segmentation | π Paper | π» Code
WS-TIS | Task: Instance Segmentation | π» Code
mQSM: Multitask Learning-Based Quantitative Susceptibility Mapping | Task: QSM reconstruction and brain region segmentation | π Paper | π» Code
Anatomy-Guided Pathology Segmentation | Task: Segmentation | π Paper | π» Code
Synchronous Image-Label Diffusion | Task: Segmentation | π Paper | π» Code
Beyond Adapting SAM: Towards End-to-End Ultrasound Image Segmentation via Auto Prompting | Task: Segmentation | π Paper | π» Code
Centerline Boundary Dice Loss for Vascular Segmentation | Task: Segmentation | π Paper | π» Code
Network Calibration | Task: segmentation | π Paper | π» Code
Class-Aware Mutual Mixup for Semi-supervised Cross-Domain Segmentation | Task: Segmentation | π Paper | π» Code
Comprehensive Generative Replay for TIL Segmentation | Task: segmentation | π Paper | π» Code
CriDiο¬: Criss-Cross Injection Diο¬usion Framework for Prostate Segmentation | Task: Segmentation | π Paper | π» Code
Voxel Scene Graph for Intracranial Hemorrhage | Task: Segmentation and Detection | π Paper | π» Code
CryoSAM | Task: Segmentation | π Paper | π» Code
CT-Based Brain Ventricle Segmentation | Task: Segmentation | π Paper | π» Code
Cut to the Mix | Task: segmentation | π Paper | π» Code
CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Differentiable Soft Morphological Filters for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Dynamic Position Transformation and Boundary Refinement Network for Left Atrial Segmentation | Task: Segmentation | π Paper | π» Code
Dynamic Pseudo Label Optimization in Nuclei Segmentation | Task: Segmentation | π Paper | π» Code
Text-Free Inference via Self-guidance | Task: Segmentation | π Paper | π» Code
Enhancing Label-Eο¬cient Medical Image Segmentation with Text-Guided Diο¬usion Models | Task: Segmentation | π» Code
MS Lesion Segmentation with Self-supervised Pre-training and Synthetic Lesion Integration | Task: segmentation | π Paper | π» Code
FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
FM-ABS: Promptable Foundation Model | Task: Segmentation | π Paper | π» Code
FRCNet | Task: Segmentation | π Paper | π» Code
H2ASeg | Task: Segmentation | π Paper | π» Code
I2Net: Exploiting Misaligned Contexts Orthogonally for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
IterMask2: Iterative Unsupervised Anomaly Segmentation for Brain Lesions | Task: Segmentation | π Paper | π» Code
Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification | Task: segmentation | π Paper | π» Code
A New Cine-MRI Segmentation Method | Task: Segmentation | π Paper | π» Code
LKM-UNet: Large Kernel Vision Mamba UNet for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Low-Rank Continual Pyramid Vision Transformer | Task: Segmentation | π Paper | π» Code
Low-Rank Mixture-of-Experts for Continual Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
LUCIDA: Low-Dose Universal-Tissue CT Image Domain Adaptation | Task: Segmentation | π Paper | π» Code
Mask-Enhanced Segment Anything Model | Task: Semantic Segmentation | π Paper | π» Code
Weakly Supervised Histological Tissue Segmentation with ARML | Task: Segmentation | π Paper | π» Code
MoreStyle: Relax Low-Frequency Constraint of Fourier-Based Image Reconstruction in Generalizable Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
CausalCLIPSeg: Unlocking CLIPβs Potential in Referring Medical Image Segmentation with Causal Intervention | Task: Segmentation | π Paper | π» Code
Multi-stage Multi-granularity Focus-Tuned Learning Paradigm for Medical HSI Segmentation | Task: Segmentation | π Paper | π» Code
NeuroLink: Bridging Weak Signals in Neuronal Imaging with Morphology Learning | Task: segmentation | π Paper | π» Code
Pair Shuffle Consistency for Semi-supervised Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
PathMamba: Weakly Supervised State Space Model for Multi-class Segmentation of Pathology Images | Task: Segmentation | π Paper | π» Code
Prompt-Based Segmentation Model | Task: Segmentation | π Paper | π» Code
Prompting Segment Anything Model with Domain-Adaptive Prototype | Task: Segmentation | π Paper | π» Code
QueryNet: A Uniο¬ed Framework for Accurate Polyp Segmentation and Detection | Task: Segmentation, Detection | π Paper | π» Code
Let Me DeCode You | Task: Segmentation | π Paper | π» Code
Test-Time Domain Adaptation for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
SDCL: Students Discrepancy-Informed Correction for Semi-supervised Medical Segmentation | Task: Segmentation | π Paper | π» Code
SegMamba: Long-Range Sequential Modeling Mamba for 3D Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
SegNeuron: 3D Neuron Instance Segmentation | Task: Segmentation | π Paper | π» Code
SelfReg-UNet for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Shortcut Learning in Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Semi-supervised Tubular Structure Segmentation | Task: Segmentation | π Paper | π» Code
SimTxtSeg: Weakly-Supervised Medical Image Segmentation with Simple Text Cues | Task: Segmentation | π Paper | π» Code
Simulation-Based Segmentation of Blood Vessels in Cerebral 3D OCTA Images | Task: Segmentation | π Paper | π» Code
Stable Diο¬usion Segmentation for Biomedical Images | Task: Segmentation | π Paper | π» Code
PRISM: A Promptable and Robust Interactive Segmentation Model | Task: Segmentation | π Paper | π» Code
Swin SMT: Global Sequential Modeling for 3D Medical Image Segmentation | Task: segmentation | π Paper | π» Code
Centerline-Cross Entropy Loss for Vessel-Like Structure Segmentation | Task: Segmentation | π Paper | π» Code
Topologically Faithful Multi-class Segmentation in Medical Images | Task: Multiclass Segmentation | π Paper | π» Code
Benchmark for Colorectal Cancer Segmentation in Endorectal Ultrasound Videos | Task: segmentation | π Paper | π» Code
TP-DRSeg: Improving Diabetic Retinopathy Lesion Segmentation with Explicit Text-Prompts Assisted SAM | Task: Segmentation | π Paper | π» Code
Unsupervised Training of Neural Cellular Automata on Edge Devices | Task: segmentation | π Paper | π» Code
Weakly-Supervised Medical Image Segmentation with Gaze Annotations | Task: Segmentation | π Paper | π» Code
FairDiο¬: Fair Segmentation with Point-Image Diο¬usion | Task: Segmentation | π Paper | π» Code
CS3: Cascade SAM for Sperm Segmentation | Task: Segmentation | π Paper | π» Code
S-SYNTH: Knowledge-Based, Synthetic Generation of Skin Images | Task: Segmentation | π Paper | π» Code
AcneAI | Task: Classification and Segmentation | π Paper | π» Code
Anatomic-Constrained Medical Image Synthesis via Physiological Density Sampling | Task: Segmentation, Image Reconstruction | π Paper | π» Code
ASA: Learning Anatomical Consistency, Sub-volume Spatial Relationships and Fine-Grained Appearance | Task: Segmentation | π Paper | π» Code
Cache-Driven Spatial Test-Time Adaptation for Cross-Modality Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Cross Prompting Consistency with Segment Anything Model for Semi-supervised Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Deep Spectral Methods for Unsupervised Ultrasound Image Interpretation | Task: Segmentation | π Paper | π» Code
Diο¬usion Models with Implicit Guidance for Medical Anomaly Detection | Task: Anomaly detection, segmentation | π Paper | π» Code
Diffusion-Enhanced Consistency Learning for Retinal Image Segmentation | Task: Segmentation | π Paper | π» Code
Few Slices Suffice | Task: Segmentation | π Paper | π» Code
HySparK | Task: Segmentation | π Paper | π» Code
IPLC: Iterative Pseudo Label Correction Guided by SAM for Source-Free Domain Adaptation in Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Learning from Partial Label Proportions | Task: Segmentation | π Paper | π» Code
Learning Representations by Maximizing Mutual Information Across Views for Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Masks and Manuscripts: Advancing Medical Pre-training | Task: Classification and segmentation | π Paper
MOST: Multi-formation Soft Masking for Semi-supervised Medical Image Segmentation | Task: segmentation | π Paper | π» Code
SaSaMIM: Synthetic Anatomical Semantics-Aware Masked Image Modeling for Colon Tumor Segmentation in NCCT | Task: Segmentation | π Paper | π» Code
Semi-supervised Segmentation in Diabetic Retinopathy | Task: segmentation | π Paper | π» Code
3D Partial Points Meets SAM | Task: segmentation | π Paper | π» Code
Brain Cortical Functional Gradients Predict Cortical Folding Patterns | Task: Segmentation | π Paper | π» Code
EM Image Denoising and Segmentation | Task: Joint Denoising and Segmentation | π Paper | π» Code
LSSNet | Task: Segmentation | π Paper | π» Code
MiHATP: A Multi-hybrid Attention Super-Resolution Network for Pathological Image | Task: Super-resolution, Segmentation | π Paper | π» Code
Boost Performance Fairness in Medical Federated Learning | Task: Segmentation | π Paper | π» Code
Conο¬dence Intervals Uncovered | Task: Segmentation | π Paper | π» Code
Federated Multi-centric Image Segmentation with Uneven Label Distribution | Task: Segmentation | π Paper | π» Code
FedEvi: Improving Federated Medical Image Segmentation via Evidential Weight Aggregation | Task: Segmentation | π Paper | π» Code
FedIA: Federated Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
FUNAvg: Federated Uncertainty Weighted Averaging for Datasets with Diverse Labels | Task: multi-label segmentation | π Paper | π» Code
MH-pFLGB: Model Heterogeneous Personalized Federated Learning via Global Bypass for Medical Image Analysis | Task: Classification, Segmentation | π Paper | π» Code
Overlay Mantle-Free for Semi-supervised Medical Image Segmentation | Task: Segmentation | π Paper | π» Code
Progressive Knowledge Distillation for Automatic Perfusion Parameter Maps Generation | Task: Segmentation | π Paper | π» Code
pFLFE: Cross-silo Personalized Federated Learning | Task: Segmentation | π Paper | π» Code
Robust Conformal Volume Estimation | Task: Segmentation | π Paper | π» Code
Reliable Source Approximation | Task: Segmentation | π Paper | π» Code
Sparse Bayesian Networks | Task: classification and segmentation | π Paper | π» Code
Single-source Domain Generalization via Lipschitz Regularization | Task: Segmentation | π Paper | π» Code
Cross-Graph Interaction and Diffusion Probability Models for Lung Nodule Segmentation | Task: segmentation | π Paper | π» Code
Characterizing the Left Ventricular Ultrasound Dynamics in the Frequency Domain | Task: Segmentation | π Paper | π» Code
Robust Semi-supervised Multimodal Image Segmentation | Task: segmentation | π Paper | π» Code
Intrapartum Ultrasound Image Segmentation of Pubic Symphysis and Fetal Head | Task: Segmentation | π Paper | π» Code
IOSSAM | Task: Segmentation | π Paper | π» Code
From Pixel to Cancer | Task: tumor segmentation | π Paper | π» Code
A Hyperreο¬ective Foci Segmentation Network for OCT Images | Task: Segmentation | π Paper | π» Code
Instance-Aware Representation for CAC Segmentation | Task: Segmentation | π Paper | π» Code
Hybrid-Structure-Oriented Transformer for Arm Musculoskeletal Ultrasound Segmentation | Task: Segmentation | π Paper | π» Code
Implicit Representation Embrces Airway Structures | Task: Segmentation | π Paper | π» Code
Improving Cross-Domain Brain Tissue Segmentation in Fetal MRI with Synthetic Data | Task: Segmentation | π Paper | π» Code
RIP-A V: Joint Representative Instance Pre-training for Retinal Artery/Vein Segmentation | Task: Segmentation | π Paper | π» Code
Brain-Shift | Task: Biomarker Extraction | π Paper | π» Code
D-CoRP: Differentiable Connectivity Refinement for Functional Brain Networks | Task: refinement | π Paper | π» Code
Eddeep: Fast Eddy-Current Distortion Correction | Task: Distortion correction | π Paper | π» Code
ESPA: An Unsupervised Harmonization Framework | Task: Harmonization | π Paper | π» Code
Enhancing Spatiotemporal Disease Progression Models via Latent Diο¬usion and Prior Knowledge | Task: disease progression modeling | π Paper | π» Code
TractOracle | Task: Tractography | π Paper | π» Code
Fusing CBCT and Intraoral Scan Data Into a Single Tooth Image | Task: Data Fusion | π Paper | π» Code
NODER: Image Sequence Regression Based on Neural Ordinary Differential Equations | Task: Regression | π Paper | π» Code
Across-Subject Ensemble-Learning Alleviates the Need for Large Samples for fMRI Decoding | Task: decoding | π Paper | π» Code
Adaptive Subtype and Stage Inference for Alzheimerβs Disease | Task: Subtype and Stage Inference | π Paper
Boosting FFPE-to-HE Virtual Staining | Task: Virtual staining | π Paper | π» Code
Large-Scale 3D Infant Face Model | Task: 3D model development | π Paper | π» Code
Medical Cross-Modal Prompt Hashing | Task: Cross-Modal Hashing | π Paper | π» Code
PhenDiff | Task: Image-to-image translation | π Paper | π» Code
Spatio-Temporal Neural Distance Fields for Conditional Generative Modeling of the Heart | Task: conditional generative modeling | π Paper | π» Code
Volume-Optimal Persistence Homological Scaffolds of Hemodynamic Networks Covary with MEG Theta-Alpha Aperiodic Dynamics | Task: topological learning | π Paper | π» Code
Deep Learning for MRS Voxel Placement in Brain Tumors | Task: Voxel Placement | π Paper
DomainAdapt: Leveraging Multitask Learning | Task: Nutritional status assessment | π Paper
Framework for Unsupervised Statistical Shape Model Learning | Task: Model Learning | π Paper | π» Code
Anatomical Structure-Guided Medical Vision-Language Pre-training | Task: Representation Learning | π Paper | π» Code
Multi-modality 3D CNN Transformer for Assisting Clinical Decision in Intracerebral Hemorrhage | Task: clinical decision support | π Paper | π» Code
Cross-conditioned Diffusion Model for Medical Image to Image Translation | Task: image-to-image translation | π Paper | π» Code
Material Decomposition in Photon-Counting CT | Task: Material Decomposition | π Paper
PASTA: Pathology-Aware MRI to PET Translation with Diffusion Models | Task: Cross-modal image translation | π Paper | π» Code
Pixel2Mechanics: Automated Biomechanical Simulations of High-Resolution Intervertebral Discs from Anisotropic MRIs | Task: Simulation | π Paper
3D Volumetric Brain CT-to-MRI Translation | Task: Image-to-image translation (I2I) | π Paper | π» Code
GCAN: Generative Counterfactual Attention-Guided Network | Task: Diagnostics | π Paper | π» Code
Interpretable-by-Design Deep Survival Analysis | Task: Disease progression modeling | π Paper | π» Code
Mask-Free Neuron Concept Annotation for Interpreting Neural Networks | Task: Interpretability | π Paper | π» Code
Overcoming Atlas Heterogeneity in Federated Learning for Connectome Modeling | Task: predictive modeling | π Paper | π» Code
Subgroup-Speciο¬c Risk-Controlled Dose Estimation in Radiotherapy | Task: regression | π Paper | π» Code
Generative Image Outpainting for FOV-Truncated CT Recovery | Task: Image Outpainting | π Paper | π» Code
Improving Cone-Beam CT Image Quality | Task: image-to-image translation | π Paper | π» Code
MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise | Task: Foundational pretraining | π Paper | π» Code
CheXtriev | Task: Retrieval | π Paper | π» Code
Symptom Disentanglement in Chest X-Ray Images | Task: Disease Progression Monitoring | π Paper | π» Code
Generating Anatomically Accurate Heart Structures via Neural Implicit Fields | Task: Shape modeling | π Paper
Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images | Task: Representation learning | π Paper | π» Code
Real-World Visual Navigation for Cardiac Ultrasound View Planning | Task: Navigation | π Paper | π» Code
We welcome contributions to this awesome list! Please feel free to submit a pull request with your suggestions for awesome AI medical imaging papers.
- Fork the repository
- Create a new branch (
git checkout -b add-new-paper) - Make your changes
- Commit your changes (
git commit -am 'Add new paper') - Push to the branch (
git push origin add-new-paper) - Create a new Pull Request
Please ensure your pull request adheres to the following guidelines:
- Make sure the paper is related to AI in medical imaging
- Provide a link to the paper and, if available, a link to the code implementation
- Use the format:
[Paper Title](link) - A short description - Add the paper to the relevant category or create a new one if needed
- Check your spelling and grammar
This project is licensed under the MIT License - see the LICENSE.md file for details.
- All the researchers and developers who have contributed to the field of AI in medical imaging
- The open-source community for making their implementations available