Neural network approach to segmentation of magnetic resonance head images

Koichi Oshio; Manbir Singh

doi:10.1002/ima.1850040207

Neural network approach to segmentation of magnetic resonance head images

Koichi Oshio, Manbir Singh

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

A novel image segmentation scheme based on a neural network has been implemented to segment magnetic resonance head images. A three‐layer perceptron‐type neural network, trained with backward error propagation algorithm was used. The scheme utilizes first‐echo intensity and computed T₂ values to construct a two‐parameter space for classification. After training on a selected slice, the method successfully segments all slices for a given subject without any further human interaction.

Original language	English
Pages (from-to)	130-134
Number of pages	5
Journal	International Journal of Imaging Systems and Technology
Volume	4
Issue number	2
DOIs	https://doi.org/10.1002/ima.1850040207
Publication status	Published - 1992 Jan 1
Externally published	Yes

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Software
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering

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10.1002/ima.1850040207

Cite this

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title = "Neural network approach to segmentation of magnetic resonance head images",

abstract = "A novel image segmentation scheme based on a neural network has been implemented to segment magnetic resonance head images. A three‐layer perceptron‐type neural network, trained with backward error propagation algorithm was used. The scheme utilizes first‐echo intensity and computed T2 values to construct a two‐parameter space for classification. After training on a selected slice, the method successfully segments all slices for a given subject without any further human interaction.",

author = "Koichi Oshio and Manbir Singh",

year = "1992",

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doi = "10.1002/ima.1850040207",

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AB - A novel image segmentation scheme based on a neural network has been implemented to segment magnetic resonance head images. A three‐layer perceptron‐type neural network, trained with backward error propagation algorithm was used. The scheme utilizes first‐echo intensity and computed T2 values to construct a two‐parameter space for classification. After training on a selected slice, the method successfully segments all slices for a given subject without any further human interaction.

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Neural network approach to segmentation of magnetic resonance head images

Abstract

ASJC Scopus subject areas

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