Information technology — Medical image-based modelling for 3D printing — Part 2: Segmentation

Technologies de l'information — Modélisation médicale à base d'images pour l'impression 3D — Partie 2: Segmentation

General Information

Status
Not Published
Current Stage
5020 - FDIS ballot initiated: 2 months. Proof sent to secretariat
Start Date
27-Nov-2023
Completion Date
27-Nov-2023
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ISO/IEC FDIS 3532-2 - Information technology — Medical image-based modelling for 3D printing — Part 2: Segmentation Released:13. 11. 2023
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REDLINE ISO/IEC FDIS 3532-2 - Information technology — Medical image-based modelling for 3D printing — Part 2: Segmentation Released:13. 11. 2023
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Standards Content (Sample)

FINAL
INTERNATIONAL ISO/IEC
DRAFT
STANDARD FDIS
3532-2
ISO/IEC JTC 1
Information technology — Medical
Secretariat: ANSI
image-based modelling for 3D
Voting begins on:
2023-11-27 printing —
Voting terminates on:
Part 2:
2024-01-22
Segmentation
Technologies de l'information — Modélisation médicale à base
d'images pour l'impression 3D —
Partie 2: Segmentation
RECIPIENTS OF THIS DRAFT ARE INVITED TO
SUBMIT, WITH THEIR COMMENTS, NOTIFICATION
OF ANY RELEVANT PATENT RIGHTS OF WHICH
THEY ARE AWARE AND TO PROVIDE SUPPOR TING
DOCUMENTATION.
IN ADDITION TO THEIR EVALUATION AS
Reference number
BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO-
ISO/IEC FDIS 3532-2:2023(E)
LOGICAL, COMMERCIAL AND USER PURPOSES,
DRAFT INTERNATIONAL STANDARDS MAY ON
OCCASION HAVE TO BE CONSIDERED IN THE
LIGHT OF THEIR POTENTIAL TO BECOME STAN-
DARDS TO WHICH REFERENCE MAY BE MADE IN
NATIONAL REGULATIONS. © ISO/IEC 2023

---------------------- Page: 1 ----------------------
ISO/IEC FDIS 3532-2:2023(E)
FINAL
INTERNATIONAL ISO/IEC
DRAFT
STANDARD FDIS
3532-2
ISO/IEC JTC 1
Information technology — Medical
Secretariat: ANSI
image-based modelling for 3D
Voting begins on:
printing —
Voting terminates on:
Part 2:
Segmentation
Technologies de l'information — Modélisation médicale à base
d'images pour l'impression 3D —
Partie 2: Segmentation
COPYRIGHT PROTECTED DOCUMENT
© ISO/IEC 2023
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
be reproduced or utilized otherwise in any form or by any means, electronic or mechanical, including photocopying, or posting on
the internet or an intranet, without prior written permission. Permission can be requested from either ISO at the address below
or ISO’s member body in the country of the requester.
RECIPIENTS OF THIS DRAFT ARE INVITED TO
ISO copyright office
SUBMIT, WITH THEIR COMMENTS, NOTIFICATION
OF ANY RELEVANT PATENT RIGHTS OF WHICH
CP 401 • Ch. de Blandonnet 8
THEY ARE AWARE AND TO PROVIDE SUPPOR TING
CH-1214 Vernier, Geneva
DOCUMENTATION.
Phone: +41 22 749 01 11
IN ADDITION TO THEIR EVALUATION AS
Reference number
Email: copyright@iso.org
BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO­
ISO/IEC FDIS 3532­2:2023(E)
Website: www.iso.org
LOGICAL, COMMERCIAL AND USER PURPOSES,
DRAFT INTERNATIONAL STANDARDS MAY ON
Published in Switzerland
OCCASION HAVE TO BE CONSIDERED IN THE
LIGHT OF THEIR POTENTIAL TO BECOME STAN­
DARDS TO WHICH REFERENCE MAY BE MADE IN
ii
  © ISO/IEC 2023 – All rights reserved
NATIONAL REGULATIONS. © ISO/IEC 2023

---------------------- Page: 2 ----------------------
ISO/IEC FDIS 3532-2:2023(E)
Contents Page
Foreword .v
Introduction . vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Abbreviated terms . 3
5 Objective of segmentation .3
5.1 Background . 3
5.2 Types of segmentation methods . 4
6 Overall segmentation process .4
6.1 General .
...

ISO/IEC FDIS 3532-2:2023(E)
2023-05-15
ISO/IEC JTC 1
Secretariat: ANSI
Date: 2023-11-13
Information technology — Medical image-based
modelingmodelling for 3D printing– —
Part 2:
Segmentation
Technologies de l'information — Modélisation médicale à base d'images pour l'impression 3D —
Partie 2: Segmentation
FDIS stage

---------------------- Page: 1 ----------------------
ISO/IEC FDIS 3532-2:2023(E)
© ISO/IEC 2023
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this
publication may be reproduced or utilized otherwise in any form or by any means, electronic or mechanical,
including photocopying, or posting on the internet or an intranet, without prior written permission. Permission can
be requested from either ISO at the address below or ISO’s member body in the country of the requester.
ISO copyright office
CP 401 • Ch. de Blandonnet 8
CH-1214 Vernier, Geneva
Phone: + 41 22 749 01 11
Fax: +41 22 749 09 47
EmailE-mail: copyright@iso.org
Website: www.iso.orgwww.iso.org
Published in Switzerland
ii © ISO/IEC 2023 – All rights reserved
ii © ISO/IEC 2023 – All rights reserved

---------------------- Page: 2 ----------------------
ISO/IEC FDIS 3532-2:2023(E)
Contents
1 Scope 1
2 Normative references 1
3 Terms and definitions 1
4 Abbreviations 2
5 Objective of segmentation 4
5.1 Background 4
5.2 Related works 4
6 Overall segmentation process 5
6.1 General 5
6.2 Step1: data preparation 5
6.3 Step2: preprocessing for segmentation 5
6.4 Step3: annotation 5
6.5 Step4: selection of segmentation network model 5
6.6 Step5: performance evaluation 5
6.7 Step6: model deployment and running 6
6.8 Step7: post-processing for segmentation 6
7 Data preparation 6
7.1 General 6
7.2 Medical image 6
7.2.1 General 6
7.2.2 CT scan 6
7.2.3 MRI scan 6
7.3 Preparation steps 6
7.3.1 General 6
7.3.2 Image acquisition 7
7.3.3 Image reconstruction 7
8 Preprocessing for segmentation 7
8.1 General 7
8.2 Intensity normalization 7
8.3 Spacing normalization 8
9 Annotation 8
9.1 Data labeling 8
9.2 Pre-processing for annotation 9
9.3 Dataset management (training and testing) 9
9.4 Augmentation 10
10 Selection of network model 10
© ISO/IEC 2023 – All rights reserved iii
© ISO/IEC 2023 – All rights reserved iii

---------------------- Page: 3 ----------------------
ISO/IEC FDIS 3532-2:2023(E)
10.1 General 10
10.2 Input patch 10
11 Evaluation 11
11.1 General 11
11.2 Evaluation metrics 11
11.3 Evaluation procedure 12
12 Deployment and running 12
13 Post-processing for segmentation 13
Annex A (informative) CT scanning conditions for orbital bone segmentation 15
Annex B (informative) Characteristics of orbital bone segmentation from CT 16
Annex C (informative) Deep learning techniques 18
Annex D (informative) Considerations for overall segmentation performance 19
Bibliography 24
iv © ISO/IEC 2023 – All rights reserved
iv © ISO/IEC 2023 – All rights reserved

---------------------- Page: 4 ----------------------
ISO/IEC FDIS 3532-2:2023(E)
Contents
Foreword . vii
Introduction . viii
Part 2: Segmentation . 1
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Abbreviated terms . 3
5 Objective of segmentation . 4
5.1 Background . 4
5.2 Types of segmentation methods . 4
6 Overall segmen
...

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