Pinned Repositories
DAFT
Dynamic Affine Feature Map Transform
Dataset-Bias
Detect and correct bias in neuroimaging
nn-common-modules
Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models
quickNAT_pytorch
PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
QuickNATv2
Fast Whole Brain Segmentation (Layers, codes and Pre-trained Models)
ReLayNet
Retinal Layers and Fluid Segmentation in Macular OCT scans (code + Pre-trained Model)
relaynet_pytorch
Pytorch Implementation of retinal OCT Layer Segmentation (with trained models)
squeeze_and_excitation
PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks
StablePose
Official Pytorch Implementation of Paper - Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation - NeurIPS 2024
Vox2Cortex
Lab for Artificial Intelligence in Medical Imaging 's Repositories
ai-med/squeeze_and_excitation
PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks
ai-med/quickNAT_pytorch
PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty
ai-med/StablePose
Official Pytorch Implementation of Paper - Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation - NeurIPS 2024
ai-med/relaynet_pytorch
Pytorch Implementation of retinal OCT Layer Segmentation (with trained models)
ai-med/Vox2Cortex
ai-med/QuickNATv2
Fast Whole Brain Segmentation (Layers, codes and Pre-trained Models)
ai-med/DAFT
Dynamic Affine Feature Map Transform
ai-med/nn-common-modules
Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models
ai-med/ReLayNet
Retinal Layers and Fluid Segmentation in Macular OCT scans (code + Pre-trained Model)
ai-med/PANIC
Prototypical Additive Neural Network for Interpretable Classification
ai-med/almgig
Adversarial Learned Molecular Graph Inference and Generation
ai-med/causal-effects-in-alzheimers-continuum
Code for the paper "Identification of causal effects of neuroanatomy on cognitive decline requires modeling unobserved confounders"
ai-med/PASTA
Official pytorch implementation of Paper - 🍝 PASTA: Pathology-Aware MRI to PET Cross-modal Translation with Diffusion Models - MICCAI 2024
ai-med/Dataset-Bias
Detect and correct bias in neuroimaging
ai-med/AbdomenNet
ai-med/DeepNAT
Caffe implementation of DeepNAT for brain segmentation
ai-med/HALOS
ai-med/abcd_study
ai-med/KeepTheFaith
ai-med/MAS-LR
Pytorch Implementation of MAS-LR, a Continual Learning approach for importance driven incremental domain learning. https://arxiv.org/abs/2005.00079
ai-med/SVEHNN
Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data (SVEHNN)
ai-med/TripletTraining
Official PyTorch Implementation for From Barlow Twins to Triplet Training: Differentiating Dementia with Limited Data - MIDL 2024
ai-med/geomdl_anatomical_mesh
ai-med/point_recalibration
ai-med/STRUDEL
ai-med/MetadataNorm
Repository for the paper "Metadata Normalization"
ai-med/OrganDETR
ai-med/pcl-protopnet-nw
Our work aims to integrate interpretability of neural networks and self-supervised learning on unlabelled datasets.