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Journal ArticleDOI

CERR: A computational environment for radiotherapy research

Joseph O. Deasy, +2 more
- 01 May 2003 - 
- Vol. 30, Iss: 5, pp 979-985
TLDR
CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.
Abstract
A software environment is described, called the computational environment for radiotherapy research (CERR, pronounced "sir"). CERR partially addresses four broad needs in treatment planning research: (a) it provides a convenient and powerful software environment to develop and prototype treatment planning concepts, (b) it serves as a software integration environment to combine treatment planning software written in multiple languages (MATLAB, FORTRAN, C/C++, JAVA, etc.), together with treatment plan information (computed tomography scans, outlined structures, dose distributions, digital films, etc.), (c) it provides the ability to extract treatment plans from disparate planning systems using the widely available AAPM/RTOG archiving mechanism, and (d) it provides a convenient and powerful tool for sharing and reproducing treatment planning research results. The functional components currently being distributed, including source code, include: (1) an import program which converts the widely available AAPM/RTOG treatment planning format into a MATLAB cell-array data object, facilitating manipulation; (2) viewers which display axial, coronal, and sagittal computed tomography images, structure contours, digital films, and isodose lines or dose colorwash, (3) a suite of contouring tools to edit and/or create anatomical structures, (4) dose-volume and dose-surface histogram calculation and display tools, and (5) various predefined commands. CERR allows the user to retrieve any AAPM/RTOG key word information about the treatment plan archive. The code is relatively self-describing, because it relies on MATLAB structure field name definitions based on the AAPM/RTOG standard. New structure field names can be added dynamically or permanently. New components of arbitrary data type can be stored and accessed without disturbing system operation. CERR has been applied to aid research in dose-volume-outcome modeling, Monte Carlo dose calculation, and treatment planning optimization. In summary, CERR provides a powerful, convenient, and common framework which allows researchers to use common patient data sets, and compare and share research results.

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Citations
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Data for TROTS - The Radiotherapy Optimisation Test Set.

TL;DR: The Radiotherapy Optimisation Test Set (TROTS) is an extensive set of problems originating from radiotherapy (radiation therapy) treatment planning, designed to investigate the multi-criteria optimisation and decision-making nature of the radiotherapy problem.
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Distinct effects of rectum delineation methods in 3D-confromal vs. IMRT treatment planning of prostate cancer

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A prospective study of differences in duodenum compared to remaining small bowel motion between radiation treatments: Implications for radiation dose escalation in carcinoma of the pancreas

TL;DR: The volume of small bowel irradiated during four-field pancreatic radiation therapy changes substantially between fractions, which suggests dose escalation may be possible, however, dose limits to the duodenum should be stricter than for other segments ofsmall bowel.
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The influence of patient positioning uncertainties in proton radiotherapy on proton range and dose distributions.

TL;DR: The present work quantitatively analyzes the influence of setup uncertainties on proton range and dose distributions in therapy of small lesions in the human brain as well as target and OAR dosimetry.
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Extending python with Fortran

TL;DR: Pyfort as mentioned in this paper is a tool for connecting Fortran routines to Python, using a syntax that is close to a subset of the Fortran 95 interface syntax, which can produce one or more Python extension modules which can then be loaded into Python, either statically or dynamically, as desired.
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