Automatic segmentation of putamen from brain MRI

Authors:
Yihui Liu;Bai Li;Dave Elliman;Paul Simon Morgan;Dorothee Auer
Affiliations:
School of Computer Science & IT, University of Nottingham, Nottingham, UK;School of Computer Science & IT, University of Nottingham, Nottingham, UK;School of Computer Science & IT, University of Nottingham, Nottingham, UK;Academic Radiology, University of Nottingham, Queen’s Medical Centre, Nottingham, UK;Academic Radiology, University of Nottingham, Queen’s Medical Centre, Nottingham, UK
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Year:
2006

Citing 2
Cited 0

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Neural Networks

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Abstract

In this paper we present an automatic segmentation of the Putamen shape from brain MRI based on wavelets and a neural network. Firstly we detect the Putamen region slice by slice using 1D wavelet feature extraction. Then fuzzy c-means technology is combined with edge detection to segment the objects inside the Putamen region. Finally features are extracted from the segmented objects and fed into a neural network classifier in order to identify the Putamen shape. Experiment shows the segmentation results to be accurate and efficient.