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A Gauss-Newton Based Approach to Automatic Beam Commissioning
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Numerical Analysis, NA.
2016 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
En Gauss-Newton-metod för automatisk maskinkommissionering (Swedish)
Abstract [en]

In computer assisted planning of radiation treatment and more specifically the software RayStation developed by RaySearch, certain kinds of model calibration problems arise. The process of solving these problems is called beam commissioning. Today beam commissioning is handled by optimizing subsets of the underlying parameters using a quasi-Newton algorithm. In this thesis we investigate the beam commissioning problem space for all of the parameters. We find that the variables are rather well behaved and therefor propose a method based on linearizing dose before scoring. This reduces the number of expensive function calls drastically and allows us to optimize with regard to all of the underlying parameters simultaneously. When using a least squares score function, the method coincides with the Gauss-Newton method, a well-known nonlinear least squares method with fast convergence properties if good starting points are available. We use this method applied to a weighted least squares approximation of our score function for two different machine models using two different dose engines. For all of our simulation experiments, the models are improved. We conclude that a method like this may be used for beam commissioning processes and that our method probably has room for improvement.

Abstract [sv]

I datorassisterad strålbehandling och mer specifikt i mjukvaran RayStation utvecklad av RaySearch, uppkommer vissa typer av kalibreringsproblem.

Processen att lösa dessa kallas maskinkommissionering. Idag hanteras problemet genom att optimera subset av de underliggande modelparametrarna med en quasi- Newton algoritm. I den här uppsatsen undersöker vi hela problemrymden associerad med maskinkommissionerings problemet. Vi finner att parametrarna beter sig ganska enkelt och föreslår på grund av detta att dosen kan linjäriseras i en punkt och poängsättas i en region omkring den punkten. Detta reducerar antalet dyra funktionsanrop kraftigt och tillåter oss att samoptimera alla modelparametrar samtidigt. Om kvadratiska straff används sammanfaller metoden med Gauss-Newton metoden, en välkänd metod med snabb konvergens om bra startvärden finns tillgängliga. Vi använder den här metoden applicerad på en viktad minstakvadratapproximation av vår poängsättningsfunktion för två maskinmodeller och två dosmotorer. För samtliga experiment är modellerna förbättrade. Vi drar slutsatsen att metoder som denna kan användas i maskinkommissionerings processenen och att det antagligen är möjligt att förbättra vår metod ytterligare.

Place, publisher, year, edition, pages
2016.
Series
TRITA-MAT-E, 2016:06
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:kth:diva-181962OAI: oai:DiVA.org:kth-181962DiVA: diva2:902335
External cooperation
RaySearch Laboratories
Subject / course
Scientific Computing
Educational program
Master of Science - Applied and Computational Mathematics
Supervisors
Examiners
Available from: 2016-02-10 Created: 2016-02-10 Last updated: 2016-02-10Bibliographically approved

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CiteExportLink to record
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