SEGMENTATION OF MR IMAGES USING NEURAL NETS

被引：16
|
作者：
TOULSON, DL
BOYCE, JF
机构：
[1] Wheatstone Laboratory, Kings College, London
来源：
IMAGE AND VISION COMPUTING | 1992年 / 10卷 / 05期
关键词：
NEURAL NETWORK; IMAGE SEGMENTATION; COOCCURRENCE MATRICES;
D O I：
10.1016/0262-8856(92)90050-D
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A two tier system for magnetic resonance (MR) image segmentation is proposed. The first stage involves probabilistically classifying the pixels of the input image based on second order grey level statistics obtained from the co-occurrence matrix. These probabilities then form the input to a multi-layer perceptron, allowing contextual constraints to be applied to local areas of the image thereby improving the spatial coherence of the classification.
引用
收藏
页码：324 / 328
页数：5
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