DocumentCode
676808
Title
Brain tumour detection using Pulse coupled neural network (PCNN) and back propagation network
Author
Subashini, M. Monica ; Sahoo, Sujit Kumar
Author_Institution
SELECT, VIT Univ., Vellore, India
fYear
2012
fDate
27-29 Dec. 2012
Firstpage
1
Lastpage
6
Abstract
Brain tumor detection is an important application in recent days. The medical problems are severe if tumor is identified at the later stage. Hence diagnosis is necessary at the earliest. MRI is the current technology which enables the detection, diagnosis and evaluation. In this work, the images obtained through MRI are segmented and then fed to a model known as Pulse coupled neural network for detecting the presence of tumor in the brain image. The physician could seek the help of this model if the input MRI brain images are more in number and the network would help the physician to save time for further analysis. The work also utilizes back propagation network for classification. Both the networks are less complex in nature and hence the processing of MRI brain images is very simple. The network classifies the input images as normal and tumor containing. The tumor may be benign and malignant and it needs medical support for further classification.
Keywords
backpropagation; biomedical MRI; image classification; image segmentation; neural nets; object detection; tumours; MRI brain images; PCNN; backpropagation network; benign tumor; brain tumour detection; image classification; image segmentation; magnetic resonance imaging; malignant tumor; pulse coupled neural network; BPN; Classification; MRI; Pulse Coupled Neural Network (PCNN); Segmentation;
fLanguage
English
Publisher
iet
Conference_Titel
Sustainable Energy and Intelligent Systems (SEISCON 2012), IET Chennai 3rd International on
Conference_Location
Tiruchengode
Electronic_ISBN
978-1-84919-797-7
Type
conf
DOI
10.1049/cp.2012.2181
Filename
6719087
Link To Document