Application of convolutional neural networks with anatomical knowledge for brain MRI analysis in MS patients

• Autorzy: Stasiak B. , Tarasiuk P. , Michalska I. , Tomczyk A.

Identyfikatory

DOI

10.24425/bpas.2018.125933

• Języki publikacji: EN

Abstrakty

EN

In this paper we consider the problem of automatic localization of multiple sclerosis (MS) lesions within brain tissue. We use a machine learning approach based on a convolutional neural network (CNN) which is trained to recognize the lesions in magnetic resonance images (MRI scans) of the patient’s brain. The training images are relatively small fragments clipped from the MRI scans so – in order to provide additional hints on location of a given clip within the brain structures – we include anatomical information in the training/testing process. Our research has shown that indicating the location of the ventricles and other structures, as well as performing brain tissue classification may enhance the results of the automatic localization of the MS-related demyelinating plaques in the MRI scans.

Słowa kluczowe

EN

multiple sclerosis; convolutional neural networks; skull stripping; ventricular system

PL

stwardnienie rozsiane; splotowe sieci neuronowe; system komorowy

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2018
• Tom: Vol. 66, nr 6
• Strony: 857--868
• Opis fizyczny: Bibliogr. 36 poz., rys., tab.

Twórcy

autor

Stasiak B.

• Institute of Information Technology, Lodz University of Technology, Wolczanska 215, 90-924 Lodz, Poland

autor

Tarasiuk P.

• Institute of Information Technology, Lodz University of Technology, Wolczanska 215, 90-924 Lodz, Poland

autor

Michalska I.

• Department of Radiology, Barlicki University Hospital, Kopcinskiego 22, 91-153 Lodz, Poland

autor

Tomczyk A.

• Institute of Information Technology, Lodz University of Technology, Wolczanska 215, 90-924 Lodz, Poland

Bibliografia

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).