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Un nuovo approccio di apprendimento profondo per il rilevamento dei tumori cerebrali

Un nuovo approccio di apprendimento profondo per il rilevamento dei tumori cerebrali

Bhavani R / Malathy T / Subraja R

54,38 €
IVA incluido
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Editorial:
KS OmniScriptum Publishing
Año de edición:
2024
Materia
Política y gobierno
ISBN:
9786207925209
54,38 €
IVA incluido
Disponible

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I tumori cerebrali rappresentano un ostacolo considerevole nel campo dell’assistenza sanitaria e richiedono una diagnosi accurata e tempestiva per ottenere una terapia efficace e migliorare i risultati dei pazienti. La risonanza magnetica (RM) e la tomografia computerizzata (TC) sono tecniche cruciali per l’identificazione dei tumori cerebrali, e ogni metodo offre vantaggi unici. Tuttavia, dipendere esclusivamente da una modalità può limitare la precisione della diagnosi. Questo progetto presenta un metodo innovativo che integra la risonanza magnetica e la tomografia computerizzata per migliorare l’individuazione e la categorizzazione dei tumori cerebrali. Utilizzando una rete neurale a convoluzione a 13 strati e algoritmi di fusione delle immagini, il nostro approccio cerca di combinare i vantaggi di entrambe le modalità, riducendo i rispettivi svantaggi. Il flusso di lavoro prevede il caricamento di scansioni MRI e CT su un’interfaccia, dove una rete neurale convoluzionale (CNN) applica l’algoritmo di fusione delle immagini nel backend. Il risultato della classificazione rivela l’esistenza, la natura o l’assenza di un tumore. Inoltre, i risultati possono essere ottenuti tramite un sito web o un’applicazione mobile, rendendo più semplice ed efficace la diagnosi dei pazienti da parte degli operatori sanitari.

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