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aims

Automatic MS lesion delineation model. nnU-Net trained on 549 clinical patientients

amyloidai

Estimation of brain amyloid accumulation using deep learning in clinical [11C]PiB PET imaging

auto_tumour_seg

Clinical evaluation of deep learning for tumour delineation on [18F]FDG-PET/CT of head and neck cancer

brainpetnr

Code used in relation to the neurodegenerative disorder study with [11C]PiB and [18F]FE-PE2I tracers (2022). Image preparation, model inference and metrics extraction.

cnn

deepmedic_dgk

Deep medic adapted to be used with PET-CT segmentation tasks

deepmrac

Deep learning based peudoCT generation from MRI

hd-ctbet

MRI brain extraction tool

hnc-tumour-seg

Clinical evaluation of deep learning for tumour delineation on [18F]FDG-PET/CT of head and neck cancer

innereye-deeplearning-dgk

Adapted from https://github.com/microsoft/InnerEye-DeepLearning

mr-check

nnunet-dgk

My additions and changes to nnUNet (my changes were eventually unused - this is mostly uploaded to document version I used)

pe2i_denoiser

Denoises PE2I lowdose PET data

rh-library

A collection of deployment ready machine learning tools developed by CAAI. Each model is packaged in rh-node to enable easy deployment with docker

rh-node

rh-node

rh-queue

rh-scripts

rh-torch

Shared scripts for training deep learning networks in torch

swinunetr-dgk

Adapted from https://github.com/Project-MONAI/research-contributions/tree/main/SwinUNETR/BTCV

tureckova-dgk

My adaptation of Tureckova's attention-gated nnUNet method to work with PET-CT data.

zerodose

zerodose