Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

    Publication Date
    Source Authors
    Source Title
    Source Issue
    Publication Date

    2017

    Source Authors

    Akkus Z, Galimzianova A, Hoogi A, Rubin D, Erickson B

    Source Title

    Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions

    Source Issue

    Journal of Digital Imaging

    vol. 30, issue 4

    Page Range: 449-459

    L’articolo si riferisce all’uso dell’Intelligenza Artificiale, è molto importante e significativo, in particolar modo quando parliamo di risoluzione e interpretazione delle immagini, legato alla riduzione degli errori, in grado di elaborare le proprie informazioni e i dati che li riguardano. alla diagnosi delle patologie renali, tramite utilizzo di nuove metodiche di studio come l’MRI e la sua efficacia. Vengono discusse le caratteristiche MRI delle lesioni celebrali comuni e meno comuni, nonché la valutazione della diffusione delle lesioni maligne e la valutazione preoperatoria. Tale elaborato risalta la gestione autonoma e responsabile della suddetta attività.Il tema cardine del brano, tratta le architetture del “Deep Learning” attualmente utilizzate per la segmentazione delle strutture cerebrali e delle sue lesioni, con la capacita di dare una corretta diagnosi con i mezzi di imaging non invasivo ad oggi a disposizione. In quanto quest’ultime, costituiscono una rilevante risorsa perché sono in rapida evoluzione e possono sostituire le datate tecniche d’imaging, che in alcuni casi possono portare ad una non corretta diagnosi. Queste problematiche, infatti, rappresentano la complicanza in assoluto più frequente in quest’ambito. Successivamente, vengono riassunti e discusse le prestazioni, la velocità e le proprietà degli approcci di apprendimento profondo del suddetto prodotto, che ci indica la possibilità di usufruire di questi metodi. Infine, viene illustrata una valutazione critica dello stato attuale e identifica i probabili sviluppi e tendenze future. Il brano si suddivide in più parti, inizialmente viene mostrata la tematica dell’argomento al fine di aumentarne la conoscenza, ed i relativi rischi ad esse associate. In prosecuzione viene sviluppato il tema centrale con i relativi obiettivi che si prefigge. Successivamente vengono evidenziati gli obiettivi che tale tematica intende raggiungere, vengono illustrate le varie tecniche e le applicazioni in MRI. Evidenziando gli avanzamenti tecnologici e metodologici in risonanza magnetica del Deep Learning.

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