Tesi etd-05062025-141031 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
MORCALDI, GIANLUCA
URN
etd-05062025-141031
Titolo
A machine learning approach to discriminate malignant and benign breast lesions using multimodal MRI
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Prencipe, Giuseppe
relatore Lizzi, Francesca
relatore Lizzi, Francesca
Parole chiave
- ensemble learning
- machine learning
- mri
- radiomics
- xgboost
Data inizio appello
30/05/2025
Consultabilità
Completa
Riassunto
The study explores using Artificial Intelligence to distinguish malignant from benign breast lesions with multimodal MRI. Using a public dataset of 200 patients, a radiomic approach has been tried to extract the features to train an XGBoost classifier, alongside the extraction of dynamic features from the kinetic curves of DCE-MRI. The model achieved an AUC of 0.90 using radiomic features alone, 0.91 using dynamic features and 0.92 when combining radiomic and dynamic features, showing the potential diagnostic improvement with both modalities
File
| Nome file | Dimensione |
|---|---|
| TESI_DEFINITIVA.pdf | 3.36 Mb |
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