Brain tumors are considered to be one of the most lethal types of tumor. Accurate segmentation of brain MRI is an important task for the analysis of neurological diseases. The mortality rate of brain tumors is increasing according to World Health Organization. Detection at early stages of brain tumors can increase the expectation of the patients’ survival. Concerning artificial intelligence approaches for clinical diagnosis of brain tumors, there is an increasing interest in segmentation approaches based on deep learning because of its ability of self-learning over large amounts of data. Deep learning is nowadays a very promising approach to develop effective solution for clinical diagnosis. This chapter provides at first some basic concepts and techniques behind brain tumor segmentation. Then the imaging techniques used for brain tumor visualization are described. Later on, the dataset and segmentation methods are discussed.

Deep learning for brain tumor segmentation / Munir, Khushboo; Frezza, Fabrizio; Rizzi, Antonello. - (2021), pp. 189-201. - STUDIES IN COMPUTATIONAL INTELLIGENCE. [10.1007/978-981-15-6321-8_11].

Deep learning for brain tumor segmentation

Munir, Khushboo
;
Frezza, Fabrizio;Rizzi, Antonello
2021

Abstract

Brain tumors are considered to be one of the most lethal types of tumor. Accurate segmentation of brain MRI is an important task for the analysis of neurological diseases. The mortality rate of brain tumors is increasing according to World Health Organization. Detection at early stages of brain tumors can increase the expectation of the patients’ survival. Concerning artificial intelligence approaches for clinical diagnosis of brain tumors, there is an increasing interest in segmentation approaches based on deep learning because of its ability of self-learning over large amounts of data. Deep learning is nowadays a very promising approach to develop effective solution for clinical diagnosis. This chapter provides at first some basic concepts and techniques behind brain tumor segmentation. Then the imaging techniques used for brain tumor visualization are described. Later on, the dataset and segmentation methods are discussed.
2021
Deep learning for cancer diagnosis
978-981-15-6320-1
978-981-15-6321-8
deep learning; convolutional neural network; brain tumor segmentation; artificial intelligence
02 Pubblicazione su volume::02a Capitolo o Articolo
Deep learning for brain tumor segmentation / Munir, Khushboo; Frezza, Fabrizio; Rizzi, Antonello. - (2021), pp. 189-201. - STUDIES IN COMPUTATIONAL INTELLIGENCE. [10.1007/978-981-15-6321-8_11].
File allegati a questo prodotto
File Dimensione Formato  
Munir_Deep-learning_2020.pdf

solo gestori archivio

Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 335.19 kB
Formato Adobe PDF
335.19 kB Adobe PDF   Contatta l'autore
Munir_copertina_Deep-learning_2020.jpg

accesso aperto

Tipologia: Altro materiale allegato
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 31.42 kB
Formato JPEG
31.42 kB JPEG

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1438603
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? ND
social impact