Title: Application of adaptive neuro-fuzzy inference systems for MR image classification and tumour detection
Authors: M. Pallikonda Rajasekaran; R. Sri Meena
Addresses: Kalasalingam University, Anand Nagar, Krishnankoil 626 190, Virudhunagar District, Tamil Nadu, India ' Kalasalingam University, Anand Nagar, Krishnankoil 626 190, Virudhunagar District, Tamil Nadu, India
Abstract: In earlier days, Magnetic-Resonance (MR) brain image classification and tumour detection was done by humans. But, this classification is impractical for large amounts of data. The uses of intelligence techniques have shown great improvement. Hence, in this paper the ANFIS is applied for classification and detection. Decision making was performed in two stages: feature extraction using Principal Component Analysis (PCA) and ANFIS trained with the backpropagation gradient descent method in combination with the least-squares method. The performance of the ANFIS classifier is evaluated in terms of training performance and classification accuracies and the results confirm that the proposed ANFIS has potential in detecting the tumours.
Keywords: medical image classification; PCA; principal component analysis; ANFIS implementation; adaptive neuro-fuzzy inference systems; MRI; magnetic resonance imaging; brain images; tumour detection; neural networks; fuzzy logic; cancer detection.
International Journal of Biomedical Engineering and Technology, 2012 Vol.9 No.2, pp.133 - 146
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 09 Jul 2012 *