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| Presentation | 2020-11-04 16:10 Performance of automated melanoma diagnosis by adding lesion information to deep convolutional neural network Ginji Hirano, Mitsutaka Nemoto, Yuich Kimura, Takashi Nagaoka (Kindai University)  MICT2020-20 MI2020-46 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Melanoma is a type of superficial tumor, which is highly malignant. Early-stage melanoma is difficult to diagnose because it looks like a benign lesion. In this study, we developed an automatic melanoma diagnostic system using the DCNN. We replaced any one of the three channels of the RGB image with the lesion image to pay attention to the lesion in the DCNN. In this study, we show the analysis results using 1000 cases of melanoma and non-melanoma. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | melanoma / Deep Learngin / VGG16 / HAM10000 / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 220, MI2020-46, pp. 62-64, Nov. 2020. | |
| Paper # | MI2020-46 | |
| Date of Issue | 2020-10-28 (MICT, MI) | |
| ISSN | 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 | MICT2020-20 MI2020-46 |
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| Conference Information | |
| Committee | MICT MI |
| Conference Date | 2020-11-04 - 2020-11-04 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical imaging technology, healthcare and medical information communication technology |
| Paper Information | |
| Registration To | MI |
| Conference Code | 2020-11-MICT-MI |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Performance of automated melanoma diagnosis by adding lesion information to deep convolutional neural network |
| Sub Title (in English) | * |
| Keyword(1) | melanoma |
| Keyword(2) | Deep Learngin |
| Keyword(3) | VGG16 |
| Keyword(4) | HAM10000 |
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| 1st Author's Name | Ginji Hirano |
| 1st Author's Affiliation | Kindai University (Kindai University) |
| 2nd Author's Name | Mitsutaka Nemoto |
| 2nd Author's Affiliation | Kindai University (Kindai University) |
| 3rd Author's Name | Yuich Kimura |
| 3rd Author's Affiliation | Kindai University (Kindai University) |
| 4th Author's Name | Takashi Nagaoka |
| 4th Author's Affiliation | Kindai University (Kindai University) |
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| Speaker | Author-1 |
| Date Time | 2020-11-04 16:10:00 |
| Presentation Time | 20 minutes |
| Registration for | MI |
| Paper # | MICT2020-20, MI2020-46 |
| Volume (vol) | vol.120 |
| Number (no) | no.219(MICT), no.220(MI) |
| Page | pp.62-64 |
| #Pages | 3 |
| Date of Issue | 2020-10-28 (MICT, MI) |
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