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...

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Vydané v:	Journal of medical systems Ročník 44; číslo 2; s. 32
Hlavní autori:	Amin, Javaria, Sharif, Muhammad, Gul, Nadia, Raza, Mudassar, Anjum, Muhammad Almas, Nisar, Muhammad Wasif, Bukhari, Syed Ahmad Chan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.02.2020 Springer Nature B.V
Predmet:	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
On-line prístup:	Získať plný text
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