Vai ai contenuti. | Spostati sulla navigazione | Spostati sulla ricerca | Vai al menu | Contatti | Accessibilità

logo del sistema bibliotecario dell'ateneo di padova

Cavinato, Samuele (2019) Tensor network methods for Radiotherapy Dose Optimization. [Magistrali biennali]

Full text disponibile come:

[img]
Preview
PDF
6Mb

Abstract

The very first successful application of tensor network methods (TNMs) to the solution of the dose optimization in Intensity Modulated Radiation Therapy (IMRT) is considered. This technique provides a method to modulate the local beam intensities, dividing the beam into smaller beamlets. This allows to reduce the radiation toxicity for healthy organs and deal with irregular and inhomogeneous tumors. Plan's goals are encoded as mathematical constraints into a cost function expressing the distance between the prescribed and delivered dose. Aim of the optimization is to minimize the function associating to each beamlet the optimal weight xj. In this thesis a classical quadratic cost function is mapped into an Insing-like Hamiltonian, where the beamlets weights are described by a system of long-range interacting qubits. The aim of the work is to solve the dose optimization problem using a binary tree tensor network (bTTN) to find the Hamiltonian's groundstate and to show the applicability of TNM to the IMRT dose optimization problem.

Item Type:Magistrali biennali
Corsi di Diploma di Laurea:Scuola di Scienze > Fisica
Uncontrolled Keywords:Binary Tree Tensor Network (bTTN), TNM, IMRT, Cancer
Subjects:Area 02 - Scienze fisiche > FIS/02 Fisica teorica, modelli e metodi matematici
Codice ID:63583
Relatore:Montangero, Simone
Correlatore:Paiusco, Marta
Data della tesi:25 November 2019
Biblioteca:Polo di Scienze > Dip. Fisica e Astronomia "Galileo Galilei" - Biblioteca
Tipo di fruizione per il documento:on-line per i full-text
Tesi sperimentale (Si) o compilativa (No)?:Yes

Solo per lo Staff dell Archivio: Modifica questo record