sft110's repositories
BayesfMRI
BayesfMRI R package
brain-segmentation-pytorch
U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI
brainchop
Brainchop: In-browser 3D MRI rendering and segmentation
fmriprep
fMRIPrep is a robust and easy-to-use pipeline for preprocessing of diverse fMRI data. The transparent workflow dispenses of manual intervention, thereby ensuring the reproducibility of the results.
freesurfer
Neuroimaging analysis and visualization suite
graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
intensity-normalization
normalize the intensities of various MR image modalities
lightning-hydra-template
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
llm-python
Large Language Models (LLMs) tutorials & sample scripts, ft. langchain, openai, llamaindex, gpt, chromadb & pinecone
mDDPM
Unsupervised Anomaly Detection in Medical Images Using Masked Diffusion Model
MRI-preprocessing-techniques
Code examples of the free course in Youtube of brain MRI preprocessing techniques in python
MRIcroGL
v1.2 GLSL volume rendering. Able to view NIfTI, DICOM, MGH, MHD, NRRD, AFNI format images.
nilearn
Machine learning for NeuroImaging in Python
pySuStaIn
Subtype and Stage Inference (SuStaIn) algorithm with an example using simulated data.
pytorch-deep-learning
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
pytorch-frame
Tabular Deep Learning Library for PyTorch
Radiology_Image_Preprocessing_for_Deep_Learning
A Quick Guide on Radiology Image Pre-processing for Deep Learning Applications in Prostate Cancer Research
smriprep
Structural MRI PREProcessing (sMRIPrep) workflows for NIPreps (NeuroImaging PREProcessing tools)
StRegA
StRegA: Unsupervised anomaly detection in brain MRIs using a compact context-encoding variational autoencoder
tutorial
MONAI Tutorials
Unsupervised_Anomaly_Detection_Brain_MRI
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study
vit_ae_plus_plus
Code base for the paper ViT-AE++: Improving Vision Transformer Autoencoder for Self-supervised Medical Image Representations
yAwareContrastiveLearning
Official Pytorch Implementation for y-Aware Contrastive Learning