Information: Join today and make your research activities more affordable! Technical workshop participation fees and annual registration fees are available at member rates.
Notice: [Important] Announcement of Changes to Registration Fee Payment and Manuscript Upload Procedures for IEICE Technical Meetings
IEICE Technical Committee Submission System
Conference Paper's Information		 Online Proceedings
[Sign in]
Tech. Rep. Archives
 Go Top Page Go Previous   [Japanese] / [English] 

Paper Abstract and Keywords
Presentation 2024-03-03 09:29
Automatic generation of PET/CT images by using large multimodal model
Yasushi Hirano, Seiya Konomi, Haku Ishida (Yamaguchi Univ.), Shoji Kido (Osaka Univ.) MI2023-32
Abstract (in Japanese) (See Japanese page) 
(in English) The purpose of this study was to reduce the workload of radiologists by developing a computer-aided diagnosis (CADx) system to assist in reading PET/CT images. In this system, we used LLaVA-v1.5-7b (LLaVA), a Large Multimodal Model (LMM), which is trained to generate a description from person or scenery images. PET/CT images and the radiologist's findings for these images were used for fine-tuning of LLaVA. The BERTScore was used to compare the similarity between the radiologist's findings and the sentences generated by the LLaVA before and after fine-tuning. The average BERTScores before and after fine-tuning were 0.621 and 0.631, respectively. The Wilcoxon signed-rank test was performed, and p=0.008 was obtained, indicating that "there is a significant difference in scores before and after fine-tuning.
Keyword (in Japanese) (See Japanese page) 
(in English) Image findings / Automatic generation / Large multimodal model / Generative AI / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 411, MI2023-32, pp. 7-10, March 2024.
Paper # MI2023-32 
Date of Issue 2024-02-25 (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 MI2023-32

Conference Information
Committee MI  
Conference Date 2024-03-03 - 2024-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) OKINAWAKEN SEINENKAIKAN 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging, etc. 
Paper Information
Registration To MI 
Conference Code 2024-03-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic generation of PET/CT images by using large multimodal model 
Sub Title (in English)  
Keyword(1) Image findings  
Keyword(2) Automatic generation  
Keyword(3) Large multimodal model  
Keyword(4) Generative AI  
Keyword(5)  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yasushi Hirano  
1st Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
2nd Author's Name Seiya Konomi  
2nd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
3rd Author's Name Haku Ishida  
3rd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
4th Author's Name Shoji Kido  
4th Author's Affiliation Osaka University (Osaka Univ.)
5th Author's Name  
5th Author's Affiliation ()
6th Author's Name  
6th Author's Affiliation ()
7th Author's Name  
7th Author's Affiliation ()
8th Author's Name  
8th Author's Affiliation ()
9th Author's Name  
9th Author's Affiliation ()
10th Author's Name  
10th Author's Affiliation ()
11th Author's Name  
11th Author's Affiliation ()
12th Author's Name  
12th Author's Affiliation ()
13th Author's Name  
13th Author's Affiliation ()
14th Author's Name  
14th Author's Affiliation ()
15th Author's Name  
15th Author's Affiliation ()
16th Author's Name  
16th Author's Affiliation ()
17th Author's Name  
17th Author's Affiliation ()
18th Author's Name  
18th Author's Affiliation ()
19th Author's Name  
19th Author's Affiliation ()
20th Author's Name  
20th Author's Affiliation ()
21st Author's Name  
21st Author's Affiliation ()
22nd Author's Name  
22nd Author's Affiliation ()
23rd Author's Name  
23rd Author's Affiliation ()
24th Author's Name  
24th Author's Affiliation ()
25th Author's Name  
25th Author's Affiliation ()
26th Author's Name / /
26th Author's Affiliation ()
()
27th Author's Name / /
27th Author's Affiliation ()
()
28th Author's Name / /
28th Author's Affiliation ()
()
29th Author's Name / /
29th Author's Affiliation ()
()
30th Author's Name / /
30th Author's Affiliation ()
()
31st Author's Name / /
31st Author's Affiliation ()
()
32nd Author's Name / /
32nd Author's Affiliation ()
()
33rd Author's Name / /
33rd Author's Affiliation ()
()
34th Author's Name / /
34th Author's Affiliation ()
()
35th Author's Name / /
35th Author's Affiliation ()
()
36th Author's Name / /
36th Author's Affiliation ()
()
Speaker Author-1 
Date Time 2024-03-03 09:29:00 
Presentation Time 12 minutes 
Registration for MI 
Paper # MI2023-32 
Volume (vol) vol.123 
Number (no) no.411 
Page pp.7-10 
#Pages 4 
Date of Issue 2024-02-25 (MI) 

[Return to Top Page]

[Return to IEICE Web Page]
The Institute of Electronics, Information and Communication Engineers (IEICE), Japan