Exploiting Heterogeneous Architectures for Rigid Image Registration

This repository contains the code relative the publication "Exploiting Heterogeneous Architectures for Rigid Image Registration" at BioCAS 2021

Testing Environment

1. We tested the code on linux-based machines (Ubuntu 18.04, CentOS 7), the paper machine is the CentOS one with 4-core Intel i7-6700 and an NVIDIA GTX 1660 Super.
2. We used python 3.6 with pydicom cv2 numpy pandas torch kronia argparse statistics packets on the generation machine
3. Data used in this publication were generated by the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC).https://doi.org/10.7937/k9/tcia.2018.pat12tbs. Patient: C3N-00704, Study: Dec 10, 2000 NM PET 18 FDG SKULL T, CT: WB STND, PET: WB 3D AC)
4. The 1+1 code takes inspiration from ITK code

Code organization

• *.py python source code for the 1+1 or Powell's optimizations procedures
• run_script.sh automation script to run extensive tests for both CPU and CUDA-based platforms

Credits and Contributors

Contributors: D'Arnese, Eleonora and Del Sozzo, Emanuele and Conficconi, Davide and Santambrogio, Marco D.

If you find this repository useful, please use the following citation(s):

@inproceedings{faberbiocas2021,
author = {D'Arnese, Eleonora and Del Sozzo, Emanuele and Conficconi, Davide and Santambrogio, Marco D.},
title = {Exploiting Heterogeneous Architectures for Rigid Image Registration},
booktitle = {2021 IEEE Biomedical Circuits and Systems Conference (BioCAS)},
pages={1--4},
year = {2021},
organization={IEEE}
}