Veuillez utiliser cette adresse pour citer ce document : http://dspace.univ-tiaret.dz:80/handle/123456789/14745
Affichage complet
Élément Dublin CoreValeurLangue
dc.contributor.authorKACEM, Mohamed-
dc.date.accessioned2024-07-21T13:13:04Z-
dc.date.available2024-07-21T13:13:04Z-
dc.date.issued2024-06-
dc.identifier.urihttp://dspace.univ-tiaret.dz:80/handle/123456789/14745-
dc.description.abstractThis thesis explores the diagnosis and treatment of brain tumors through advanced imaging techniques and deep learning algorithms. Brain cancer, a severe condition affecting the central nervous system, requires precise diagnostic methods for effective treatment. This work focuses on the segmentation of brain tumors from MRI images using state-of-the-art deep learning models. The proposed method integrates pre-trained convolutional neural networks, improving segmentation accuracy and robustness. Our results demonstrate significant advancements in the accuracy and efficiency of brain tumor diagnosis and provide a foundation for future research in this critical medical field.en_US
dc.language.isoenen_US
dc.publisherIbn Khaldoun Universityen_US
dc.subjectBrain Tumoren_US
dc.subjectDeep Learningen_US
dc.subjectConvolutional Neural Networksen_US
dc.subjectMedical Imagingen_US
dc.titleBrain Tumor Segmentation Using Neural Networks convolutional (CNN)en_US
dc.typeThesisen_US
Collection(s) :Master

Fichier(s) constituant ce document :
Fichier Description TailleFormat 
TH.M.INF.2024.04.pdf874,25 kBAdobe PDFVoir/Ouvrir


Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.