Paper Abstract and Keywords |
Presentation |
2019-09-05 10:35
[Short Paper]
Dynamic PET Image Reconstruction using Non-Negative Matrix Decomposition with Deep Image Prior Tomoshige Shimomura, Kazuya Kawai (NIT), Muneyuki Sakata (Tokyo Metro. Inst. Gerontology), Yuichi Kimura (KU), Tatsuya Yokota, Hidekata Hontani (NIT) PRMU2019-24 MI2019-43 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
We present a PET image reconstruction method that can reconstruct dynamic PET images with high SN ratio and can simultaneously segment the images into regions each of which has a different ligand dynamics. It is known that PET image reconstruction is highly sensitive with measurement noises included in sinograms and that stable PET image reconstruction needs appropriate constraints over the solution space. The proposed method constrains the temporal patterns of each voxel using the quadratic variation and the spatial patterns using a Deep Image Prior. For introducing these constraints of the solution space, the proposed method represents each of the temporal series of sinograms and of corresponding PET images using a matrix and factorizes the latter matrix into bases of spatial and temporal patterns. Here, the non-negative constraint is also introduced in the factorization. This non-negative matrix factorization enables the segmentation of the spatial patterns based on the difference of the temporal patterns. In this presentation, we describe the algorithm and show some experimental results. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
PET image / Image reconstruction / Deep Image Prior / Non-negative matrix factorization / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 193, MI2019-43, pp. 69-70, Sept. 2019. |
Paper # |
MI2019-43 |
Date of Issue |
2019-08-28 (PRMU, 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) |
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PRMU2019-24 MI2019-43 |
Conference Information |
Committee |
PRMU MI IPSJ-CVIM |
Conference Date |
2019-09-04 - 2019-09-05 |
Place (in Japanese) |
(See Japanese page) |
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(See Japanese page) |
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Paper Information |
Registration To |
MI |
Conference Code |
2019-09-PRMU-MI-CVIM |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Dynamic PET Image Reconstruction using Non-Negative Matrix Decomposition with Deep Image Prior |
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Keyword(1) |
PET image |
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Image reconstruction |
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Deep Image Prior |
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Non-negative matrix factorization |
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1st Author's Name |
Tomoshige Shimomura |
1st Author's Affiliation |
Nagoya Institute of Technology (NIT) |
2nd Author's Name |
Kazuya Kawai |
2nd Author's Affiliation |
Nagoya Institute of Technology (NIT) |
3rd Author's Name |
Muneyuki Sakata |
3rd Author's Affiliation |
Tokyo Metropolitan Institute of Gerontology (Tokyo Metro. Inst. Gerontology) |
4th Author's Name |
Yuichi Kimura |
4th Author's Affiliation |
Kindai University (KU) |
5th Author's Name |
Tatsuya Yokota |
5th Author's Affiliation |
Nagoya Institute of Technology (NIT) |
6th Author's Name |
Hidekata Hontani |
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Nagoya Institute of Technology (NIT) |
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Speaker |
Author-1 |
Date Time |
2019-09-05 10:35:00 |
Presentation Time |
10 minutes |
Registration for |
MI |
Paper # |
PRMU2019-24, MI2019-43 |
Volume (vol) |
vol.119 |
Number (no) |
no.192(PRMU), no.193(MI) |
Page |
pp.69-70 |
#Pages |
2 |
Date of Issue |
2019-08-28 (PRMU, MI) |
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