Radiotherapy

This code and datasets are to support the paper “Predicting Respiratory Motion for Controlling Radiotherapy Treatment: an algorithmic approach” by T. Krilavicius, I. Zliobaite, A. Vidugiriene, H. Simonavicius and L. Jarusevicius, currently under review at Artificial Intelligence in Medicine journal.

The code and datasets can be used for research purposes, provided that following source is cited:
“T. Krilavicius, I. Zliobaite, A. Vidugiriene, H. Simonavicius and L. Jarusevicius. (2013). Predicting Respiratory Motion for Controlling Radiotherapy Treatment: an algorithmic approach. Technical report. Baltic Institute of Advanced Technologies.
or
“T. Krilavicius, I. Zliobaite, A. Vidugiriene, H. Simonavicius and L. Jarusevicius. (2015). Predicting respiratory motion for real-time tumour tracking in radiotherapy. Arxiv. http://arxiv.org/abs/1508.00749″

The code (in MATLAB) and datasets are available at http://datasets.bpti.lt/radiotherapy .

Contact: t.krilavicius@bpti.lt

Last updated 2015 10 12.

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CONTENTS

  • DATA (this folder contains datasets)
  • ALGORITHMS (contains stand alone implementations of the algorithms)
  • EXPERIMENTS (contains the sources for reproducing the experiments reported in the paper)
  • readme.txt (the same as text in this page)

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Instructions for reproducing experiments

Folder EXPERIMENTS contains scripts for reproducing two experiments:
1) run_compare_predictors.m –> compares different prediction methods, the results are reported in Figure 2 and Tables A.1 and A.2;
2) run_evaluate_algorithm.m –> evaluates the proposed algorithmic solution, the results are reported in Figure 6, Tables 4 and A.3.

Parameters of the methods can be changed in parameter_settings.m

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