| Paper Abstract and Keywords |
| Presentation |
2012-09-02 11:00
Medical image diagnosis of liver cancer by revised GMDH-type neural network self-organizing neural network architectures using heuristic self-organization Tadashi Kondo, Junji Ueno, Shoichiro Takao (Tokushima Univ.) PRMU2012-32 IBISML2012-15 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In this study, a feedback Group Method of Data Handling (GMDH)-type neural network self-organizing neural network architecture using heuristic self-organization is proposed. Feedback GMDH-type neural network algorithm has an ability of self-selecting optimum neuron architecture from three neuron architectures such as sigmoid function neuron, radial basis function (RBF) neuron and polynomial neuron. Feedback GMDH-type neural network also have abilities of self-selecting the number of feedback loop calculations, the number of neurons in hidden layers and useful input variables. This algorithm is applied to medical image diagnosis of liver cancer. First, normal regions of liver are recognized and extracted using the feedback GMDH-type neural network and the regions of liver are extracted after the post-processing analysis for output image. Then, a new another GMDH-type neural network is organized using the extracted liver image and the candidate image regions of liver cancer are extracted. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
GMDH / Medical image diagnosis / Neural Network / / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 112, no. 197, PRMU2012-32, pp. 17-22, Sept. 2012. |
| Paper # |
PRMU2012-32 |
| Date of Issue |
2012-08-26 (PRMU, IBISML) |
| ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
PRMU2012-32 IBISML2012-15 |
| Conference Information |
| Committee |
PRMU IBISML IPSJ-CVIM |
| Conference Date |
2012-09-02 - 2012-09-03 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
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| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
PRMU |
| Conference Code |
2012-09-PRMU-IBISML-CVIM |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Medical image diagnosis of liver cancer by revised GMDH-type neural network self-organizing neural network architectures using heuristic self-organization |
| Sub Title (in English) |
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| Keyword(1) |
GMDH |
| Keyword(2) |
Medical image diagnosis |
| Keyword(3) |
Neural Network |
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| 1st Author's Name |
Tadashi Kondo |
| 1st Author's Affiliation |
The University of Tokushima (Tokushima Univ.) |
| 2nd Author's Name |
Junji Ueno |
| 2nd Author's Affiliation |
The University of Tokushima (Tokushima Univ.) |
| 3rd Author's Name |
Shoichiro Takao |
| 3rd Author's Affiliation |
The University of Tokushima (Tokushima Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2012-09-02 11:00:00 |
| Presentation Time |
30 minutes |
| Registration for |
PRMU |
| Paper # |
PRMU2012-32, IBISML2012-15 |
| Volume (vol) |
vol.112 |
| Number (no) |
no.197(PRMU), no.198(IBISML) |
| Page |
pp.17-22 |
| #Pages |
6 |
| Date of Issue |
2012-08-26 (PRMU, IBISML) |