Nothing Special   »   [go: up one dir, main page]

Skip to content

mvallieres/radiomics

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

41 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

 ___              ____    _____    ____     _    _   _____    ___     __
|   |     /\     |    \     |     /    \   | \  / |    |     /   \   /  |
|___|    /  \    |     |    |    |      |  |  \/  |    |    |        \__
|  \    /____\   |     |    |    |      |  |      |    |    |           \
|   \  /      \  |____/   __|__   \____/   |      |  __|__   \___/   |__/

-------------------------------------------------------------------------

|<https://github.com/mvallieres/radiomics/>|
--> A package providing MATLAB programming tools for radiomics analysis.

-------------------------------------------------------------------------
REFERENCES:
[1] Vallières, M. et al. (2015). A radiomics model from joint FDG-PET and 
    MRI texture features for the prediction of lung metastases in soft-tissue 
    sarcomas of the extremities. Physics in Medicine and Biology, 60(14), 
    5471-5496. doi:10.1088/0031-9155/60/14/5471

[2] Zhou, H., Vallières, M., Bai, H.X. et al. (2017). MRI features predict
    survival and molecular markers in diffuse lower-grade gliomas.      
    Neuro-Oncology, 19(6), 862-870. doi:10.1093/neuonc/now256

[3] Vallière, M. et al. (2017). Radiomics strategies for risk assessment  
    of tumour failure in head-and-neck cancer. Scientific Reports,
    7:10117. doi:10.1038/s41598-017-10371-5 
-------------------------------------------------------------------------
AUTHOR: Martin Vallières <mart.vallieres@gmail.com>
-------------------------------------------------------------------------
HISTORY:
- Version 1.0: May 2015
-------------------------------------------------------------------------
DISCLAIMER:
"I'm not a programmer, I'm just a scientist doing stuff!"
-------------------------------------------------------------------------


*** THANK YOU FOR YOUR INTEREST IN THIS PACKAGE ***
--> If you have any questions, comments or suggestions about this package, 
    please do not hesitate to contact me!


This package contains 5 folders:

1. 'TextureToolbox': MATLAB codes to perform texture analysis from an input 
    2D or 3D region of interest (ROI). This toolbox is self-contained and 
    can be used on its own outside of the radiomics package. In particular,
    this texture analysis package implements wavelet band-pass filtering, 
    isotropic resampling, discretization length corrections and different 
    quantization tools. Please see ref. [1] for more details.


2. 'NonTextureFeatures': MATLAB codes to compute features other than textures
    from an input 3D region of interest (ROI). Include features such as SUV 
    metrics, AUC-CSH, Percent Inactive, Size, Solidity, Volume and Eccentricity. 
    Please see ref. [1] for more details.


3. 'MultivariableModeling': MATLAB codes to perform multivariable analysis
    operations such as logistic regression, bootstrapping, feature set 
    reduction, feature set selection, prediction performance estimation, etc.


4. 'Utilities': MATLAB codes used to perform different operations including
    the computation of SUV maps, reading of directory containing DICOM imaging
    data, conversion of RTstruct DICOM objects to 3D masks, etc.


5. 'STUDIES': MATLAB codes used for specific studies. To reproduce the 
    experiments of a given study, please see its corresponding folder.
   
    - 'STS_study': Ref. [1]
		   A. Imaging/ROI data and clinical information is 
       	              available on The Cancer Imaging Archive (TCIA) website 
                      under the following DOI: 
		      <http://dx.doi.org/10.7937/K9/TCIA.2015.7GO2GSKS>.
    - 'LGG_study': Ref. [2]
		   A. Texture data ("TEXTURES_TCGA.zip") is available
                      on Google Drive: 
                      <https://drive.google.com/open?id=0B0fcZCGXT3nZWXM5d0t3OXVjQzA>
		   B. Imaging data is available on the TCIA website:
		      <http://doi.org/10.7937/K9/TCIA.2016.L4LTD3TK>
		   C. ROI data is available on the TCIA website:
		      <https://doi.org/10.7937/K9/TCIA.2017.BD7SGWCA>
    - 'HN_study':  Ref. [3]
		   A. Imaging/ROI data and clinical information is available
                      on the TCIA website:
		      <http://doi.org/10.7937/K9/TCIA.2017.8oje5q00>

***************************************************************************
ACKNOWLEDGEMENTS: other software code
- Wei's GLRLM toolbox: Xunkai Wei, Gray Level Run Length Matrix Toolbox
  v1.0, Software,Beijing Aeronautical Technology Research Center, 2007.
  <http://www.mathworks.com/matlabcentral/fileexchange/17482-gray-level-run-length-matrix-toolbox>
- Q. Li: <http://www.mathworks.com/matlabcentral/fileexchange/23377-ellipsoid-fitting>
- CERR development team: <http://www.cerr.info/>
- Dirk-Jan Kroon (imresize3D.m): <http://www.mathworks.com/matlabcentral/fileexchange/21451-multimodality-non-rigid-demon-algorithm-image-registration/content//functions/imresize3d.m>
- David Reshef and Yakir Reshef: MINE version 1.0.1d <http://www.exploredata.net/> 
- DREES development team: <http://www.cerr.info/drees>
- Enric Junqué de Fortuny (fastAUC.cpp): <http://www.mathworks.com/matlabcentral/fileexchange/41258-faster-roc-auc>
- François Beauducel (roundsd.m): <http://www.mathworks.com/matlabcentral/fileexchange/26212-round-with-significant-digits>
- Jos van der Geest (herrorbar.m): <http://www.mathworks.com/matlabcentral/fileexchange/3963-herrorbar> 
***************************************************************************

About

MATLAB programming tools for radiomics analysis

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages