A New Sulcus Extraction Algorithm Using MAGNET Principle

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概要

• 論文の詳細を見る

• This paper presents a feature extraction model 'MAGNET' to find the deepest point of branched sulcus. Our model demonstrates magnetic principle and consists of four types of ideal magnetic poles : an N-pole and three S-poles. According to attractive or repulsive Coulomb forces between their poles, one of the S-poles is pushed to the deepest point of the sulcus. First, we explain our model on the simple sulcus model. Second, we apply it to the sulcus with implicit branches. Our model can detect the target points in every branch. Then an example to realize the model on a synthetic image is introduced. We apply our model to human brain MR images and human foot CT images. Experimental results on human brain MR images show that our method enable us to successfully detect the points.

• 社団法人電子情報通信学会の論文
• 1998-11-25

著者

• Hata Yutaka

  The Authors Are With Department Of Computer Engineering Himeji Institute Of Technology : The Author

• Kamiura Naotake

  The Authors Are With Department Of Computer Engineering Himeji Institute Of Technology

• Hirano Shoji

  The Authors Are With Department Of Computer Engineering Himeji Institute Of Technology

関連論文

• A Learning Algorithm with Activation Function Manipulation for Fault Tolerant Neural Networks
• On a Weight Limit Approach for Enhancing Fault Tolerance of Feedforward Neural Networks
• A New Sulcus Extraction Algorithm Using MAGNET Principle

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