Brain Tumor Detection by Using Stacked Autoencoders in Deep Learning

Brain tumor detection depicts a tough job because of its shape, size and appearance variations. In this manuscript, a deep learning model is deployed to predict input slices as a tumor (unhealthy)/non-tumor (healthy). This manuscript employs a high pass filter image to prominent the inhomogeneities...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Journal of medical systems Jg. 44; H. 2; S. 32
Hauptverfasser:	Amin, Javaria, Sharif, Muhammad, Gul, Nadia, Raza, Mudassar, Anjum, Muhammad Almas, Nisar, Muhammad Wasif, Bukhari, Syed Ahmad Chan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.02.2020 Springer Nature B.V
Schlagworte:	Brain cancer Brain tumors Deep learning Glioma Health Informatics Health Informatics and Computer Vision Health Sciences Image & Signal Processing Medicine Medicine & Public Health Recent Advances in Deep Learning for Biomedical Signal Processing Statistics for Life Sciences Tumors Softmax Hidden size Glioma Stacked sparse autoencoder Magnetic resonance images
ISSN:	0148-5598, 1573-689X, 1573-689X
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!