Lab for Artificial Intelligence in Medical Imaging

squeeze_and_excitation

PyTorch Implementation of 2D and 3D 'squeeze and excitation' blocks for Fully Convolutional Neural Networks

quickNAT_pytorch

PyTorch Implementation of QuickNAT and Bayesian QuickNAT, a fast brain MRI segmentation framework with segmentation Quality control using structure-wise uncertainty

relaynet_pytorch

Pytorch Implementation of retinal OCT Layer Segmentation (with trained models)

StablePose

Official Pytorch Implementation of Paper - Stable-Pose: Leveraging Transformers for Pose-Guided Text-to-Image Generation

Vox2Cortex

QuickNATv2

Fast Whole Brain Segmentation (Layers, codes and Pre-trained Models)

DAFT

Dynamic Affine Feature Map Transform

nn-common-modules

Pytorch Implementations of Common modules, blocks and losses for CNNs specifically for segmentation models

ReLayNet

Retinal Layers and Fluid Segmentation in Macular OCT scans (code + Pre-trained Model)

PANIC

Prototypical Additive Neural Network for Interpretable Classification

almgig

Adversarial Learned Molecular Graph Inference and Generation

causal-effects-in-alzheimers-continuum

Code for the paper "Identification of causal effects of neuroanatomy on cognitive decline requires modeling unobserved confounders"

PASTA

Official pytorch implementation of Paper - 🍝 PASTA: Pathology-Aware MRI to PET Cross-modal Translation with Diffusion Models - MICCAI 2024

Dataset-Bias

Detect and correct bias in neuroimaging

AbdomenNet

DeepNAT

Caffe implementation of DeepNAT for brain segmentation

abcd_study

HALOS

KeepTheFaith

MAS-LR

Pytorch Implementation of MAS-LR, a Continual Learning approach for importance driven incremental domain learning. https://arxiv.org/abs/2005.00079

SVEHNN

Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data (SVEHNN)

geomdl_anatomical_mesh

point_recalibration

STRUDEL

TripletTraining

Official PyTorch Implementation for From Barlow Twins to Triplet Training: Differentiating Dementia with Limited Data - MIDL 2024

MetadataNorm

Repository for the paper "Metadata Normalization"

OrganDETR

pcl-protopnet-nw

Our work aims to integrate interpretability of neural networks and self-supervised learning on unlabelled datasets.