This contribution illustrates the preliminary results of the research activities carried out within the PhD in Information and Communication Technology for Health (ICTH) on the topic of Delivery Manager of Cognitive Computing for Neuroncology, at the Department of Electrical Engineering and Information Technologies (DIETI) of the University of Naples “Federico II”. Main goal of this research activity is the development of computational models based on Visual Recognition and Cognitive Computing algorithms for the analysis of Magnetic Resonance Imaging (MRI) derived data in patients with brain neoplasm of unknown origin, in order to obtain a semi-supervised classification model which allows the timely identification of various brain tumors types, requiring therapeutic strategies and clinical-radiological monitoring different from each other. The final purpose of this research activity is to propose a cognitive computing-based support able to supplement information that can help the neuroradiologist in decision-making for daily clinical practice.
Cognitive computing tools for identification and classification of brain tumors starting from Magnetic Resonance Imaging: preliminary results / Russo, Camilla; Maresca, Paolo; Marinelli, Alfredo. - 2022 IEEE 21st Mediterranean Electrotechnical Conference (MELECON):(2022), pp. 595-599. [10.1109/MELECON53508.2022.9842916]
Cognitive computing tools for identification and classification of brain tumors starting from Magnetic Resonance Imaging: preliminary results
Camilla RussoPrimo
;Paolo MarescaSecondo
;Alfredo MarinelliUltimo
2022
Abstract
This contribution illustrates the preliminary results of the research activities carried out within the PhD in Information and Communication Technology for Health (ICTH) on the topic of Delivery Manager of Cognitive Computing for Neuroncology, at the Department of Electrical Engineering and Information Technologies (DIETI) of the University of Naples “Federico II”. Main goal of this research activity is the development of computational models based on Visual Recognition and Cognitive Computing algorithms for the analysis of Magnetic Resonance Imaging (MRI) derived data in patients with brain neoplasm of unknown origin, in order to obtain a semi-supervised classification model which allows the timely identification of various brain tumors types, requiring therapeutic strategies and clinical-radiological monitoring different from each other. The final purpose of this research activity is to propose a cognitive computing-based support able to supplement information that can help the neuroradiologist in decision-making for daily clinical practice.File | Dimensione | Formato | |
---|---|---|---|
Abstract_MELECON22_v.05.02.22.doc
accesso aperto
Licenza:
Creative commons
Dimensione
1.17 MB
Formato
Microsoft Word
|
1.17 MB | Microsoft Word | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.