GaoxingZheng

MedSAM

Segment Anything in Medical Images

pyCirclize

Circular visualization in Python (Circos Plot, Chord Diagram, Radar Chart)

SynthSeg

Contrast-agnostic segmentation of MRI scans

brainchop

Brainchop: In-browser 3D MRI rendering and segmentation

Dcm2Bids

Reorganising NIfTI files from dcm2niix into the Brain Imaging Data Structure

PDFChat

The PDFChat app allows you to chat with your PDF files in natural language.

Simple-Brain-Plot

brainPlot is a MATLAB function to create simple line-art brain plots.

neuroHarmonize

Harmonization tools for multi-site neuroimaging analysis. Implemented as a python package. Harmonization of MRI, sMRI, dMRI, fMRI variables with support for NIFTI images. Complements the work in Neuroimage by Pomponio et al. (2019).

cbrain

CBRAIN is a flexible Ruby on Rails framework for accessing and processing of large data on high-performance computing infrastructures.

QSM

Hongfu Sun's MATLAB codes for QSM reconstruction pipeline.

qsm-tools

List of open-source quantitative susceptibility mapping (QSM) MRI software packages and data

MRIcroWeb

NIfTI volume rendering using WebGL

ukftractography

MALPEM

MALPEM whole-brain segmentation framework

OpenMAP-T1

Whole Brain Segmentation and Parecllation Using OpenMAP-T1 Method for 3D T1 Brain MRI

multi-shell-dMRIharmonization

Harmonization of multi-shell diffusion MRI, an enhancement of https://github.com/pnlbwh/dMRIharmonization

dmriqcpy

Diffusion MRI Quality Check in python

ML-MEA-2024

ML-MEA-2024

diffusion-pipeline

Diffusion pipeline

dTractSeg

A TractSeg pipeline compatible with PyDesigner outputs

phybers

Config files for my GitHub profile.

freewater_flow

deepparcellation

DeepParcellation: deep learning for robust brain MRI parcellation of elderly East Asians

PSC

neuro_lifespan_trajectories

Interactive visualization of volumetric-age trends for anatomical brain regions.

pysphinxdoc

API Documentation Generation Tool.

pipelines

Zalesky2020

Data and script for demonstrating the operation of the SIFT and SIFT2 algorithms on the phantom structure presented in: Zalesky et al., "A cautionary note on the use of SIFT in pathological connectomes".

Zalesky2020b

Data, code and images clarifying the operation of the SIFT and SIFT2 methods on the examples presented in the publication: Zalesky et al. "SIFT in pathological connectomes: Follow-up response to Smith and colleagues"

volBrainPPCScripts