Name: Physimals group, University of Nottingham
Type: Organization
Bio: The Physimals group applies inference (estimation) techniques from information engineering to biomedical data, primarily with a view to clinical application.
Location: Nottingham, UK
Blog: https://physimals.github.io/physimals
Physimals group, University of Nottingham's Projects
Documentation for ASL tools (BASIL, oxford_asl, etc)
Model-free deconvolution for multi-TE ASL data
ASL practical for the FSL course
ASL primer exercises as made available via the Primer website (hosted on FMRIB webserver)
Module capturing scripts used for creating virtual machines in Azure for online courses
Script to run kinetic modelling on PASL/pCASL data using Fabber
Code to define a Docker container that can be used to run Basil within the QMENTA platform
XNAT plugin to support running Basil tools on data in XNAT
Custom script to convert ASL DICOM files from Phillips scanners which do not go through DCM2NIIX properly
Developmental version of ExploreASL
Matlab wrapper interface for the Fabber Bayesian model fitting tool
Framework for Bayesian model fitting using the Variational Bayes method and pluggable forward models
Forward models using the Fabber framework for Arterial Spin Labelling MRI
CEST model for the Fabber model fitting tool
Fabber models for cerebrovascular reactivity from BOLD data + PETCO2
DCE models for the Fabber model fitting tool
DSC models for fabber
Fabber models for diffusion weighted imaging
PET models for the Fabber bayesian model fitting tool
Fabber models for Quantitative BOLD MRI
Models for generating T1 maps using the Fabber model fitting tool
This is a mirror.
ASL pipeline for the Human Connectome Project
Github Pages for ibme-qubic organization
Simple linear iterative clustering (SLIC) in a region of interest (ROI)
Jupyter notebook based machine learning tutorial for the NMedIA image analysis module
Python based ASL pipeline based on oxford_asl