CUDA-accelerated Python utilities for high-throughput PET/MR image reconstruction and analysis.
Project description
NiftyPET is a Python software platform, offering high-throughput PET image reconstruction ( Python package nipet – a core package of NiftyPET) as well as image processing and analysis (Python package nimpa: https://github.com/pjmark/NIMPA) for PET/MR imaging with high quantitative accuracy and precision. The software is written in CUDA C and embedded in Python C extensions.
The scientific aspects of this software are covered in two open-access publications:
NiftyPET: a High-throughput Software Platform for High Quantitative Accuracy and Precision PET Imaging and Analysis Neuroinformatics (2018) 16:95. https://doi.org/10.1007/s12021-017-9352-y
Rapid processing of PET list-mode data for efficient uncertainty estimation and data analysis Physics in Medicine & Biology (2016). https://doi.org/10.1088/0031-9155/61/13/N322
NiftyPET includes two stand-alone and independent Python packages: NIPET and NIMPA, which are dedicated to high-throughput image reconstruction and analysis of brain images, respectively. Strong emphasis is put on the data, which are acquired using positron emission tomography (PET) and magnetic resonance (MR), especially the hybrid and simultaneous PET/MR scanners.
This software platform covers the entire processing pipeline, from the raw list-mode (LM) PET data through to the final image statistic of interest (e.g., regional SUV), including LM bootstrapping and multiple reconstructions to facilitate voxel-wise estimation of uncertainties.
In order to facilitate all the functionality, NiftyPET relies on third-party software for image conversion from DICOM to NIfTI (dcm2niix) and image registration (NiftyReg). The additional software is installed automatically to a user specified location.
Dependencies
NIMPA relies on GPU computing using NVidia’s CUDA platform. The CUDA routines are wrapped in Python C extensions. The provided software has to be compiled from source (done automatically) for any given Linux flavour (Linux is preferred over Windows) using Cmake.
The following software has to be installed prior to NIMPA installation:
CUDA (currently the latest is 9.1): https://developer.nvidia.com/cuda-downloads
Cmake (version 3.xx): https://cmake.org/download/
Python with the recommended Anaconda distribution: https://www.anaconda.com/download
Installation
To install NIMPA from source for any given CUDA version and operating system (Linux is preferred), simply type:
pip install --no-binary :all: --verbose nipetUsage
from niftypet import nipet
from niftypet import nimpaAuthor: Pawel J. Markiewicz
Copyright 2018
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
