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Paper Abstract and Keywords
Presentation 2008-01-25 10:10
A Method for Extraction of Corresponding Point Pairs among Lung Vessels in Multi-temporal Helical CT Data
Hiroshi Hanaizumi (Hosei University) MI2007-64
Abstract (in Japanese) (See Japanese page) 
(in English) A lung cancer screening system, in which two sets of multi-temporal helical CT data were co-registered and subtracted to detect temporal shape change, has been developed. In order to detect tumor accurately, we have to register lung vessels in one data set onto the other precisely. In the system, branching points of lung vessels, which were extracted by Successive Region Growing (SGR), were used as corresponding points. Lung regions in each data set were divided into many trigonal pyramids, respectively, whose vertices were the corresponding points. Then, 3D Affine transformation was applied to all corresponding trigonal pairs for smooth registration between them. Subtraction of them gave us the shape change (i.e. candidate of tumor) between two data sets. One of remaining problems was low performance in finding corresponding pair of branching points. Here, a new method was proposed to realize efficient matching among branching point sets. In the CT data, lung vessels were represented as two parts; one wass root block near interpenetration region of vessels into lung and the others branches come out from the root. In the multi-temporal data, branches had discrepancy in position and direction, but root blocks had almost the same shape. So, only the root blocks without branches were firstly co-registered. This registration enabled us to find corresponding pair of branches following the root blocks, respectively. Branching points were traced along these branches and minimum distance point pairs of the branching points were obtained as initial corresponding pairs for the registration. These pairs were iteratively updated by using the minimum distance pairing like the ICP algorithm. The fixed corresponding point pairs are used to divide each lung area into trigonal pyramids, respectively. In this paper, principle and procedures of the method are described. Application results of the method to actual multi-temporal helical CT data were also shown.
Keyword (in Japanese) (See Japanese page) 
(in English) Screening / Registration / ICP algorithm / Shape change extraction / / / /  
Reference Info. IEICE Tech. Rep., vol. 107, no. 461, MI2007-64, pp. 7-12, Jan. 2008.
Paper # MI2007-64 
Date of Issue 2008-01-18 (MI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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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Conference Information
Committee MI  
Conference Date 2008-01-25 - 2008-01-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Naha-Bunka-Tenbusu 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Medical Imaging 
Paper Information
Registration To MI 
Conference Code 2008-01-MI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Method for Extraction of Corresponding Point Pairs among Lung Vessels in Multi-temporal Helical CT Data 
Sub Title (in English)  
Keyword(1) Screening  
Keyword(2) Registration  
Keyword(3) ICP algorithm  
Keyword(4) Shape change extraction  
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1st Author's Name Hiroshi Hanaizumi  
1st Author's Affiliation Hosei University (Hosei University)
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Speaker Author-1 
Date Time 2008-01-25 10:10:00 
Presentation Time 10 minutes 
Registration for MI 
Paper # MI2007-64 
Volume (vol) vol.107 
Number (no) no.461 
Page pp.7-12 
#Pages
Date of Issue 2008-01-18 (MI) 


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