Niñerola Baizán, AidaAndrés Rodríguez, Arnau2023-07-182023-07-182023-06https://hdl.handle.net/2445/200775Treballs Finals de Grau de Física, Facultat de Física, Universitat de Barcelona, Curs: 2023, Tutora: Aida Niñerola BaizanThis 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 conducted5 p.application/pdfengcc-by-nc-nd (c) Andrés, 2023http://creativecommons.org/licenses/by-nc-nd/3.0/es/Aprenentatge profundTomografiaCàncer d'endometriTreballs de fi de grauDeep learningTomographyEndometrial cancerBachelor's thesesAutomatic segmentation of regions of interest with Deep Learning for postoperative endometrial carcinoma treatmentinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess