Presentation 2011-01-20
Proposal of a novel boosting algorithm regularized by a global shape and its performance evaluation
Kiyo SHINDO, Akinobu SHIMIZU, Hidefumi KOBATAKE, Shigeru NAWANO, Kenji SHINOZAKI,
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Abstract(in English) A conventional ensemble learning based segmentation often outputs unnatural shape, because of voxel-wise discrimination independent to its neighboring voxels. This study proposes an ensemble learning algorithm that minimizes not only error-related loss but also global shape-related loss. Actually the shape-related loss is defined as a summation of squared difference over an image between an extracted result in each learning stage and its reconstructed image from a shape sub-space. It is expected that an extracted shape becomes natural by minimizing a loss function with the shape-related loss. This paper shows effectiveness of the proposed algorithm by using a synthetic image. In addition, it presents results of applying this method to actual three dimensional CT images followed by discussion about the superiority against a conventional loss function without any shape-related loss.
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Keyword(in English) Boosting / ensemble / shape / CT / Spleen / Segmentation
Paper # MI2010-116
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Committee MI
Conference Date 2011/1/12(1days)
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Paper Information
Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Proposal of a novel boosting algorithm regularized by a global shape and its performance evaluation
Sub Title (in English)
Keyword(1) Boosting
Keyword(2) ensemble
Keyword(3) shape
Keyword(4) CT
Keyword(5) Spleen
Keyword(6) Segmentation
1st Author's Name Kiyo SHINDO
1st Author's Affiliation Tokyo University of Agriculture and Technology()
2nd Author's Name Akinobu SHIMIZU
2nd Author's Affiliation Tokyo University of Agriculture and Technology
3rd Author's Name Hidefumi KOBATAKE
3rd Author's Affiliation Tokyo University of Agriculture and Technology
4th Author's Name Shigeru NAWANO
4th Author's Affiliation International University of Health and welfare
5th Author's Name Kenji SHINOZAKI
5th Author's Affiliation National Kyusyu Cancer Center
Date 2011-01-20
Paper # MI2010-116
Volume (vol) vol.110
Number (no) 364
Page pp.pp.-
#Pages 6
Date of Issue