Graph Neural Network Library for PyTorch

AI Toolkit for Healthcare Imaging

Medical image registration using deep learning

code for MICCAI 2019 paper 'Uncertainty-aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation'.

[IJCAI'18] Unsupervised Cross-Modality Domain Adaptation of ConvNets for Biomedical Image Segmentations with Adversarial Loss (code&data)

[TMI'20, AAAI'19] Synergistic Image and Feature Adaptation

[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

Neural Rendering for Stereo 3D Reconstruction of Deformable Tissues in Robotic Surgery

Holistic Adaptation of SAM from 2D to 3D for Promptable Medical Image Segmentation

Autofocus Layer for Semantic Segmentation

Domain Generalization via Model-Agnostic Learning of Semantic Features

[TMI'20] Semi-supervised Medical Image Classification with Relation-driven Self-ensembling Model

[MICCAI'20] Shape-aware Meta-learning for Generalizing Prostate MRI Segmentation to Unseen Domains & A Well-organized Multi-site Dataset

Implementation of "Harmonizing Transferability and Discriminability for Adapting Object Detectors" (CVPR 2020)

[TMI'20] Unpaired Multi-modal Segmentation via Knowledge Distillation

Anchor optimization for RetinaNet.

Image-and-Spatial Transformer Networks

Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)

[AAAI'22] HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images

[IEEE JBHI'20] Contrastive Cross-site Learning with Redesigned Net for COVID-19 CT Classification

[ICRA 2023] Demonstration-Guided Reinforcement Learning with Efficient Exploration for Task Automation of Surgical Robot

[ICCV'21] SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them [NeurIPS 2020]

FedUL: Federated Learning from Only Unlabeled Data with Class-Conditional-Sharing Clients

[NeurIPS'23] Uncertainty Estimation for Safety-critical Scene Segmentation via Fine-grained Reward Maximization

[IJHCS'19] Webthetics: Webpage Aesthetics Quantification with Deep Learning

[AAAI'19] Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation