izpis_h1_title_alt

Musculoskeletal images classification for detection of fractures using transfer learning
Kandel, Ibrahem (Avtor), Castelli, Mauro (Avtor), Popovič, Aleš (Avtor)

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Izvleček
The classification of the musculoskeletal images can be very challenging, mostly when it is being done in the emergency room, where a decision must be made rapidly. The computer vision domain has gained increasing attention in recent years, due to its achievements in image classification. The convolutional neural network (CNN) is one of the latest computer vision algorithms that achieved state-of-the-art results. A CNN requires an enormous number of images to be adequately trained, and these are always scarce in the medical field. Transfer learning is a technique that is being used to train the CNN by using fewer images. In this paper, we study the appropriate method to classify musculoskeletal images by transfer learning and by training from scratch. We applied six state-of-the-art architectures and compared their performance with transfer learning and with a network trained from scratch. From our results, transfer learning did increase the model performance significantly, and, additionally, it made the model less prone to overfitting.

Jezik:Angleški jezik
Ključne besede:informatika, programiranje, prenos znanja, neuroscience
Vrsta gradiva:Članek v reviji (dk_c)
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:EF - Ekonomska fakulteta
Leto izida:2020
Št. strani:str. 1-14
Številčenje:Vol. 6, iss 11 (art. 127)
UDK:659.2:004
ISSN pri članku:2313-433X
DOI:10.3390/jimaging6110127 Povezava se odpre v novem oknu
COBISS.SI-ID:39651587 Povezava se odpre v novem oknu
Licenca:CC BY 4.0
To delo je dosegljivo pod licenco Creative Commons Priznanje avtorstva 4.0 Mednarodna
Število ogledov:30
Število prenosov:21
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Gradivo je del revije

Naslov:Journal of imaging
Skrajšan naslov:J. imaging
Založnik:MDPI AG
ISSN:2313-433X
COBISS.SI-ID:525653017 Povezava se odpre v novem oknu

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije (ARRS)
Številka projekta:P5-0410
Naslov:Digitalizacija kot gonilo trajnostnega razvoja posameznika, organizacij in družbe

Financer:FCT - Fundação para a Ciência e a Tecnologia, I.P.
Številka projekta:DSAIPA/DS/0022/2018
Naslov:GADgET

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:informatika, programiranje, prenos znanja, kognitivna znanost

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