Brain tumor classification using deep CNN features via transfer learning

• Published in: Computers in biology and medicine Vol. 111; p. 103345
• Main Authors: Deepak, S., Ameer, P.M.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.08.2019; Elsevier Limited
• Subjects: Accuracy; Algorithms; Brain; Brain cancer; Brain research; Brain tumor; Brain tumors; Breast cancer; Classification; Computer-aided diagnosis; Concept learning; Conflicts of interest; Convolutional neural network; Datasets; Deep learning; Feature extraction; Glioma; Image classification; Image retrieval; Learning; Magnetic resonance imaging; Measurement methods; Medical diagnosis; Medical imaging; Meningioma; Neural networks; NMR; Nuclear magnetic resonance; Pituitary; Pituitary gland; Support vector machine; Transfer learning; Tumors; Wavelet transforms; Brain tumor; Support vector machine; Transfer learning; Convolutional neural network; Computer-aided diagnosis

Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for medical applications. This paper focuses on a 3-class classification problem to differentiate among glioma, meningioma and pituitary tumors, which form three prominent types of brain tumor. The proposed classifi...