Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/200775
Title: Automatic segmentation of regions of interest with Deep Learning for postoperative endometrial carcinoma treatment
Author: Andrés Rodríguez, Arnau
Director/Tutor: Niñerola Baizán, Aida
Keywords: Aprenentatge profund
Tomografia
Càncer d'endometri
Treballs de fi de grau
Deep learning
Tomography
Endometrial cancer
Bachelor's theses
Issue Date: Jun-2023
Abstract: This project aims to evaluate deep learning algorithms’ suitability to correctly delineate the regions of interest on computer tomography images for dosimetric computations, in the context of postoperative endometrial carcinoma treatment. To achieve this goal, the project includes the complete training and evaluation of two deep learning networks. Furthermore, a qualitative assessment of the predicted dosimetric computations and a post-processing of the predicted results have been conducted
Note: Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2023, Tutora: Aida Niñerola Baizan
URI: http://hdl.handle.net/2445/200775
Appears in Collections:Treballs Finals de Grau (TFG) - Física

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