ISO/IEC 3532-1

Information technology — Medical image-based modelling for 3D printing — Part 1: General requirements

Technologies de l'information — Modélisation médicale à base d'images pour l'impression 3D — Partie 1: Exigences générales

General Information

• Status: Not Published
• ICS: 25.030 - Additive manufacturing
• ICS: 35.240.80 - IT applications in health care technology
• Technical Committee: ISO/IEC JTC 1 - Information technology
• Drafting Committee: ISO/IEC JTC 1/WG 12 - 3D Printing and scanning
• Current Stage: 6000 - International Standard under publication
• Completion Date: 20-Apr-2023

Standards Content (Sample)

ISO/IEC JTC 1 -N:2021(E) Style Definition: Heading 1: Indent: Left: 0 cm, First line:

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ISO/IEC DIS FDIS 3532-1:20212023(E)
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ISO/IEC JTC 1
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Date: 2022-09-082023-02
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Information technology —Medical image-based modelling for 3D printing – Part 1: General

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ISO/IEC DISFDIS 3532-1:20212023(E)
Formatted
© ISO 20212023, Published in Switzerland

All rights reserved. Unless otherwise specified, 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
Ch. de Blandonnet 8 • CP 401
CH-1214 Vernier, Geneva, Switzerland
Tel. + 41 22 749 01 11
Fax + 41 22 749 09 47
[e-mail]
www.iso.org
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ISO/IEC DISFDIS 3532-1:20212023(E)
Contents

Foreword ................................................................................................................................................................. iv

Introduction ............................................................................................................................................................. v

1 Scope ............................................................................................................................................................ 1

2 Normative references .............................................................................................................................. 1

3 Terms, definitions and abbreviated terms ........................................................................................ 1

3.1 Terms and definitions ............................................................................................................................. 1

3.2 Abbreviated terms.................................................................................................................................... 4

4 Overview of image processing for the medical industry ............................................................... 5

4.1 Process flow ............................................................................................................................................... 5

4.1.1 3D printing process for medical applications .................................................................................. 5

4.1.2 Explanation of a typical use case (cranial implant case) ............................................................... 6

5 General requirements ............................................................................................................................. 6

6 Requirements of data processing......................................................................................................... 7

6.1 Medical image data flow ......................................................................................................................... 7

6.2 Medical image acquisition/computed tomography scan .............................................................. 8

6.3 Segmentation ............................................................................................................................................. 9

6.4 3D reconstruction and visualization ................................................................................................. 10

6.5 Calibration and validation of 2D and 3D conversion .................................................................... 12

6.6 File format ................................................................................................................................................ 12

Annex A (Informative) Reporting ................................................................................................................... 13

Bibliography .......................................................................................................................................................... 14

Foreword .................................................................................................................................................................. v

Introduction ............................................................................................................................................................ vi

1 Scope ............................................................................................................................................................ 1

2 Normative references .............................................................................................................................. 1

3 Terms, definitions and abbreviated terms ........................................................................................ 1

3.1 Terms and definitions ............................................................................................................................. 1

3.2 Abbreviated terms.................................................................................................................................... 4

4 Overview of image processing for the medical industry ............................................................... 5

4.1 Process flow ............................................................................................................................................... 5

4.1.1 3D printing process for medical applications .................................................................................. 5

4.1.2 Explanation of a typical use case (cranial implant case) ............................................................... 6

5 General requirements ............................................................................................................................. 7

6 Requirements of data processing......................................................................................................... 7

6.1 Medical image data flow ......................................................................................................................... 7

6.2 Medical image acquisition/computed tomography scan ............................................................ 10

6.3 Segmentation ........................................................................................................................................... 10

6.4 3D reconstruction and visualization ................................................................................................. 12

6.5 Calibration and validation of 2D and 3D conversion .................................................................... 13

6.6 File format ................................................................................................................................................ 14

Annex A (informative) Reporting ................................................................................................................... 15

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ISO/IEC DISFDIS 3532-1:20212023(E)

Bibliography .......................................................................................................................................................... 16

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ISO/IEC DISFDIS 3532-1:20212023(E)
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Foreword

ISO (the International Organization for Standardization) and IEC (the International Electrotechnical

Commission) form the specialized system for worldwide standardization. National bodies that are

members of ISO or IEC participate in the development of International Standards through technical

committees established by the respective organization to deal with particular fields of technical activity.

ISO and IEC technical committees collaborate in fields of mutual interest. Other international

organizations, governmental and non-governmental, in liaison with ISO and IEC, also take part in the

work.

The procedures used to develop this document and those intended for its further maintenance are

described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria needed for the

different types of document should be noted. This document was drafted in accordance with the editorial

rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives or
www.iec.ch/members_experts/refdocs).

Attention is drawn to the possibility that some of the elements of this document may be the subject of

patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent rights. Details

of any patent rights identified during the development of the document will be in the Introduction and/or

on the ISO list of patent declarations received (see www.iso.org/patents) or the IEC list of patent

declarations received (see https://patents.iec.ch).

Any trade name used in this document is information given for the convenience of users and does not

constitute an endorsement.

For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and

expressions related to conformity assessment, as well as information about ISO's adherence to the World

Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see

www.iso.org/iso/foreword.html. In the IEC, see www.iec.ch/understanding-standards.

This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology.

A list of all parts in the ISO/IEC 3532 series can be found on the ISO and IEC websites.

Any feedback or questions on this document should be directed to the user’s national standards body. A

complete listing of these bodies can be found at www.iso.org/members.html and www.iec.ch/national-

committees.
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ISO/IEC DISFDIS 3532-1:20212023(E)
Introduction

This document was developed in response to the need for customization of 3D scanning and 3D printing

technology within the medical industry, which can be achieved by taking full advantage of information

and communication technology (ICT).

This document addresses the overview of medical image processing and requirements for image-based

modelling. 3D printing technology has caused a revolution in health care delivery. New classes of medical

devices embody the true meaning of personalized medicine. Medical device designers and practitioners

are able to practically and efficiently create devices that were very difficult or impossible to create before.

In addition to using 3D printing technology to create standard medical devices with features like intricate

lattice structures, clinicians and engineers work in conjunction to produce what are known as patient-

specific devices or patient-matched devices. These are medical devices designed to fit a specific patient’s

anatomy, typically using medical imaging from that patient. Anatomically matched devices have very

complex geometrical contours and shapes. Several challenges exist in the design process between the

input data and the final device design. Most of these steps definitely depend on software-based

management of medical images.

Overall, the world revenue from 3D printing technology in the healthcare industry is expected to grow

exponentially, yet very few guides exist for 3D printing for medical practice. Medical images from the

human body are different from solid objects due to the non-geometric nature of the human body. To

perform 3D printing for medical practice, an accurate and consistent approach for image processing and

data creation from medical images is needed. Standardization for 3D printing processes in medicine is

urgently required for education, diagnosis, neurosurgical treatment, developing simulation models,

medical equipment (including surgical guides) and surgical implantable devices in the clinical fields.

Regulatory bodies from several countries (US, Korea, Repulic of Korea, etc.) have already published their

own guidelines for approval. However, those guidelines are not specifically designed for 3D printing

technology.

Applications of 3D printing in medicine are booming, such as surgical simulation models, surgical guides,

educational models, surgical implants, etc. Those which are manufactured by 3D printing technology

require patient- and/or procedure-specific data (e.g. planned surgical technique and others) and medical

image data acquisition processing. Most of the processing of medical images for 3D printing medical

devices is software-based. In order to accurately and consistently visualize human body anatomy,

appropriate software-based modelling for 3D printing is needed. This document provides requirements

of software-based medical image processing for the purpose of producing 3D models for 3D printing.

Valuable information related to optimized medical image data for additive manufacturing can be found

in ISO/ASTM TR 52916. Formatted: std_publisher
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FINAL DRAFT INTERNATIONAL STANDARD ISO/IEC DISFDIS 3532-1:20212023(E)
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Information Technology —technology — Medical Image-Based
Modellingimage-based modelling for 3D printing– — Part 1:
General Requirementsrequirements
1 Scope

This document specifies the requirements for medical image-based modelling for 3D printing for

medical applications. It concerns accurate 3D data modelling in the medical field using medical image

data generated from computed tomography (CT) devices. It also specifies the principal considerations for

the general procedures of medical image-based modelling. It excludes soft tissue modelling from

magnetic resonance image (MRI).
2 Normative references

The following documents are referred to in the text in such a way that some or all of their content

constitutes requirements of this document. For dated references, only the edition cited applies. For

undated references, the latest edition of the referenced document (including any amendments) applies.

ISO/IEC 2382:2015, Information technology — Vocabulary

ISO/ASTM/ 52900:2021, Additive manufacturing –— General principles –— Fundamentals and

Vocabulary
3 Terms, definitions and abbreviated terms

For the purposes of this document, the terms and definitions given in ISO/IEC 2382:2015, ISO/ASTM Formatted: std_publisher

52900:2021, and the following apply.
Formatted: std_docNumber

ISO and IEC maintain terminology databases for use in standardization at the following addresses:

Formatted: std_publisher
Formatted: std_docNumber
— ISO Online browsing platform: available at https://www.iso.org/obp
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— IEC Electropedia: available at https://www.electropedia.org/
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Kingdom)
3.1 3.1 Terms and definitions
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Roman
3.1.1
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image acquisition

scanning of the structure of interest using computed tomography (CT), magnetic resonance imaging or

other three-dimensional imaging technology
[SOURCE: ISO 21227-1:2003(en), 3.4]
3.1.2
slice distance
slice spacing

distance between the centre of the slices, which is calculated by the difference in the slice locations of two

adjacent slices
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ISO/IEC DISFDIS 3532-1:20212023(E)
3.1.3
hard tissue

tissue which is mineralized and has a firm intercellular matrix (such as bone, tooth enamel, dentin and

cementum)
3.1.4
soft tissue

tissue that connects, supports or surrounds other structures and organs of the body, excluding hard tissue

Formatted: Font: Italic
(3.1.3)
3.1.5
solid organ

organ which has firm tissue consistency such as the heart, kidney, liver, lungs, and pancreas, etc.,

excluding hollow organs (such as the organs of the gastrointestinal tract) and tissue with liquid

consistency (such as blood)
3.1.6
pixel
picture element

smallest two-dimensional element of a display image that can be independently assigned attributes such

as color and intensity

[SOURCE: ISO/IEC 2382:2015, 13.03.08]2125999, modified — Notes to entry have been removed.] Formatted: English (United States)

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3.1.7
States)
voxel
Formatted: English (United States)
volume element

smallest three-dimensional element in volume or volumetric (solid) modeling that can be independently

assigned attributes such as colour and intensity

[SOURCE: ISO/IEC 2382:2015, 13.03.09]2126000, modified — Notes to entry have been removed; "solid" Formatted: Default Paragraph Font

has been replaced by "volume or volumetric (solid)".]
3.1.8
vector data
vector image
vector model

digital description of 2D image or 3D model stored as a series of points and mathematical functions to

describe the geometric figure

[SOURCE: ISO 12651-1:2012, 4.139, modified — “3D model” has been added, points"image" has been

replaced by “vertices”]"2D image or 3D model”.]
3.1.9
raster data
raster image
raster model
bitmap data
bitmap image
bitmap model

2D image or 3D model data formed by a set of picture elements (3.1.6) or volume elements (3.1.7) arranged Formatted: Font: Italic

in a grid pattern
Formatted: Font: Italic

[SOURCE: ISO 12651-1:2012, 4.18, modified — “3D model” and “volume elements” has been added]

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ISO/IEC DISFDIS 3532-1:20212023(E)
3.1.10
volume model
solid model

three-dimensional geometric model which deals with the solid characteristics of an object in order to

represent its internal structure as well as its external shapes

Note 1 to entry: Solid modeling;See ISO/IEC 2382 for definitions of volume modeling: terms and definition

standardized by ISO/IEC [ISO/IEC 2382-13:1996; ISO/IEC 2382-24:1995].solid modeling.

Note 2 to entry: Volume model can be represented with raster model (3.1.9) or vector model. (3.1.8).

Formatted: Font: Italic
Formatted: Font: Italic
3.1.11
surface model
boundary model
data set of a model which represents the surfaces of objects

Note 1 to entry: See ISO/IEC 2382 for definitions of surfacing; and surface modeling: terms and definition

standardized by ISO/IEC [ISO/IEC 2382-13:1996; ISO/IEC 2382-24:1995]..
3.1.12
facet model
faceted model
surface model (3.1.11) of which surfaces consist of group of polygons
Note 1 to entry: A triangle is widely used as a polygon.
3.1.13
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text, Don't adjust space between Asian text and numbers
segmentation
process of separating the objects of interest from their surroundings

Note 1 to entry: Segmentation can be applicable to 2D, 3D, raster or vector data. (3.1.8).

Formatted: Font: Italic
3.1.14
3D visualization

presentation intended for human viewing of a scene on a flat display surface, using graphics techniques

to convey depth information and knowledge of the arrangement and shapes of the visualized scene in a

three-dimensional space

Note 1 to entry: The graphics techniques can include use of perspective, occlusion, stereoscopy, lighting and

environmental effects, and ability to navigate the viewpoint to alternate positions and orientations.

3.1.15
3D modelling

activity intended to create a digital representation of the form and arrangement of one or more 3D objects

in a three-dimensional space.

Note 1 to entry: 3D Models maymodels can contain geometric information such as mesh vertices, appearance,

lighting, and animation information. The created representation is a prerequisite to creating a 3D visualization

Formatted: Font: Italic
(3.1.14) of the modelled objects.
3.1.16
maximum intensity projection
MIP
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ISO/IEC DISFDIS 3532-1:20212023(E)

scientific visualization method for 3D data that projects in the visualization plane the voxels with

maximum intensity that fall in the way of parallel rays traced from the viewpoint to the plane of

projection.
3.1.17
minimum intensity projection
MinIP

data visualization method that enables detection of low-density structures in a given volume.

Note 1 to entry: The algorithm uses all the data in a volume of interest to generate a single two-dimensional

image. In other words, it consists of projecting the voxel with the lowest attenuation value on every view throughout

the volume onto a 2D image.
3.1.18
Hounsfield Valuevalue
Hounsfield Unitunit

an integer representing the intensity of the image at each image point ([pixel) (3.1.6)] which originates Formatted: Font: Italic

from the x-ray scanning process and in turn represents the image intensity which in turn depends on the

density of the tissue at that location.

Note 1 to entry: Hounsfield values rise monotonically with tissue density but are not linearly proportional to

density.

Note 2 to entry: The highest range of biological tissue Hounsfield values is for cortical bone, and they can go even

higher for image artefacts such as metallic implants, metallic sections of a hospital bed included in the image, etc.

3.1.19
multiplanar reformation
MPR

two-dimensional reformatted images that are reconstructed secondarily in arbitrary planes from the

stack of axial image data.

Note 1 to entry: Multiplanar reformation (MPR) allows images to be created from the original axial plane in either

Formatted: Tab stops: 2.8 cm, Left
the coronal, sagittal, or oblique plane.
3.1.20
volume rendering

set of techniques used to display a 2D projection of a 3D discretely sampled data set, typically a 3D scalar

field
3.2 3.2 Abbreviated terms
Formatted: No bullets or numbering
2D two-dimensional
3D three-dimensional
AM additive manufacturing
AMF additive manufacturing file format
ANN artificial neural network
CAD computer aided design
CT computed tomography
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ISO/IEC DISFDIS 3532-1:20212023(E)
DICOM digital imaging and communications in medicine
HU Hounsfield unit
PACS picture archiving communication system
QC quality control
ROI region of interest
STL stereolithography
SVM support vector machine
4 Overview of image processing for the medical industry
4.1 4.1 Process flow
Formatted: No bullets or numbering
4.1.1 4.1.1 3D printing process for medical applications

In general, the medical 3D printing processing flow can be divided into eight phases, as shown in Figure 1. Formatted: cite_fig

Formatted: cite_fig
1) Image acquisition phase
Formatted: Font: Bold

In the image acquisition phase, medical images are acquired from medical imaging devices such as CT.

2) Segmentation phase Formatted: Font: Bold

In the segmentation phase, the acquired medical images are segmented to fit the design purpose and are

processed to be divided (segmented) to extract a subset that would represent the part(s) of the anatomy

under consideration.
3) 3D modelling phase
Formatted: Font: Bold

In the 3D modelling phase, the segmented data representing the human tissue is converted Formatted: Body Text, Tab stops: Not at 1.4 cm + 2.1 cm

+ 2.8 cm + 3.5 cm + 4.2 cm + 4.9 cm + 5.6 cm + 6.3 cm +
(reconstructed) into a 3D model optimized for 3D printing.
7 cm
4) 3D printing phase
Formatted: Font: Bold

In the 3D printing phase, 3D printing is performed using the 3D model designed. For this phase 3D model

is processed for 3D printing by slicing, assigning build parameters, being oriented and placed within the

build space, and can have support structures generated.
5) Post-processing phase
Formatted: Font: Bold

In the post-processing phase, the 3D printed part is post-processed to become fit for actual medical use.

6) Quality control (QC) phase Formatted: Font: Bold
Formatted: Font: Bold

In the QC phase, the 3D printed part is finally verified to meet all requirements

Formatted: Font: Bold
(user/design/quality/risk).
7) Clinical application and review phase Formatted: Font: Bold

In the clinical application and review phase, the 3D printed part is reviewed as applicable to clinical

application by the healthcare practitioner.
8) Post-market phase
Formatted: Font: Bold

In the post-marketing stage, the 3D printed part is managed based on the post-sale market management

policy according to product life cycle issues such as tracking management/recall.

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ISO/IEC DISFDIS 3532-1:20212023(E)
4.1.2 4.1.2 Explanation of a typical use case (cranial implant case)
Formatted: No bullets or numbering

Computed tomography (CT) is a common imaging modality for medical applications. For instance, for

patients with a skull defect visiting a neurosurgical clinic, CT has been known as the gold standard for

investigating bone-related problems. Figure 1 shows that the CT images are initially transferred to the

PACS server asin DICOM file format. DICOM images have been used to reconstruct 3D image through

segmentation and 3D modelling by certain software. This 3D modelled image is transformed and

exported to design software as a stereolithography (STL) file. After completion and confirmation of 3D

cranial implant by designing software, a metal AM machine builds this implant as designed. Post-

processing such as heat treatment, machining, cleaning and sanding is performed. Reverse engineering

is performed to confirm the completeness of the implant before delivery by 3D scanning and matching to

the original digital blueprint. After quality controlQC, the implant is packed, sterilized, and delivered. An

operation is performed to cover the defect with the 3D printed cranial implant. For this medical 3D

printing process, accuracy and reproducibility should be considered. The accuracy and reproducibility of

the parts (anatomical model, surgical guides, implant, etc.) from medical 3D printed parts are affected by

the sum of errors introduced in each step during data flow. These steps can be image acquisition,

segmentation, and any subsequent post-processing of the segmented images. This document scope

covers the processes 1, 2 and 3 of Fig. as shown in Figure 1, ending with a 3D model of the relevant patient Formatted: cite_fig

anatomy for use in multiple other later processes. Activities related to items for processes 4, 5, 6, 7 and -

8 are addressed by ISO/TC 261 standards. .
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ISO/IEC DISFDIS 3532-1:20212023(E)

Figure 1 — Typical workflow of medical 3D printing (example: cranial implant case)

5 General requirements

To comply withconform to this document, all of the following items shall be considered and relevant

selectioninformation shall be documented.

— — The medical image acquisition protocol by the CT scanner. Formatted: Indent: Left: 0 cm, Hanging: 1.34 cm, No

bullets or numbering, Tab stops: 1.4 cm, Left
— The clinical purpose (bone/hard tissue) of image-based modelling.
— T
...

FINAL
INTERNATIONAL ISO/IEC
DRAFT
STANDARD FDIS
3532-1
ISO/IEC JTC 1
Information technology — Medical
Secretariat: ANSI
image-based modelling for 3D
Voting begins on:
2023-02-22 printing —
Voting terminates on:
Part 1:
2023-04-19
General requirements
RECIPIENTS OF THIS DRAFT ARE INVITED TO
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THEY ARE AWARE AND TO PROVIDE SUPPOR TING
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BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO-
ISO/IEC FDIS 3532-1:2023(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
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ISO/IEC FDIS 3532-1:2023(E)
FINAL
INTERNATIONAL ISO/IEC
DRAFT
STANDARD FDIS
3532-1
ISO/IEC JTC 1
Information technology — Medical
Secretariat: ANSI
image-based modelling for 3D
Voting begins on:
printing —
Voting terminates on:
Part 1:
General requirements
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or ISO’s member body in the country of the requester.
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BEING ACCEPTABLE FOR INDUSTRIAL, TECHNO­
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LOGICAL, COMMERCIAL AND USER PURPOSES,
DRAFT INTERNATIONAL STANDARDS MAY ON
Published in Switzerland
OCCASION HAVE TO BE CONSIDERED IN THE
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DARDS TO WHICH REFERENCE MAY BE MADE IN
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ISO/IEC FDIS 3532-1:2023(E)
Contents Page

Foreword ........................................................................................................................................................................................................................................iv

Introduction .................................................................................................................................................................................................................................v

1 Scope ................................................................................................................................................................................................................................. 1

2 Normative references ..................................................................................................................................................................................... 1

3 Terms, definitions and abbreviated terms .............................................................................................................................. 1

3.1 Terms and definitions ...................................................................................................................................................................... 1

3.2 Abbreviated terms .............................................................................................................................................................................. 4

4 Overview of image processing for the medical industry .......................................................................................... 5

4.1 Process flow .............................................................................................................................................................................................. 5

4.1.1 3D printing process for medical applications ........................................................................................... 5

4.1.2 Explanation of a typical use case (cranial implant case) ................................................................ 5

5 General requirements .................................................................................................................................................................................... 6

6 Requirements of data processing ......................................................................................................................................................7

6.1 Medical image data flow ................................................................................................................................................................ 7

6.2 Medical image acquisition/computed tomography scan .................................................................................. 8

6.3 Segmentation ........................................................................................................................................................................................... 9

6.4 3D reconstruction and visualization ............................................................................................................................... 11

6.5 Calibration and validation of 2D and 3D conversion .........................................................................................12

6.6 File format ............................................................................................................................................................................................... 13

Annex A (informative) Reporting .........................................................................................................................................................................14

Bibliography .............................................................................................................................................................................................................................15

iii
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ISO/IEC FDIS 3532-1:2023(E)
Foreword

ISO (the International Organization for Standardization) and IEC (the International Electrotechnical

Commission) form the specialized system for worldwide standardization. National bodies that are

members of ISO or IEC participate in the development of International Standards through technical

committees established by the respective organization to deal with particular fields of technical

activity. ISO and IEC technical committees collaborate in fields of mutual interest. Other international

organizations, governmental and non­governmental, in liaison with ISO and IEC, also take part in the

work.

The procedures used to develop this document and those intended for its further maintenance

are described in the ISO/IEC Directives, Part 1. In particular, the different approval criteria

needed for the different types of document should be noted. This document was drafted in

accordance with the editorial rules of the ISO/IEC Directives, Part 2 (see www.iso.org/directives or

www.iec.ch/members_experts/refdocs).

Attention is drawn to the possibility that some of the elements of this document may be the subject

of patent rights. ISO and IEC shall not be held responsible for identifying any or all such patent

rights. Details of any patent rights identified during the development of the document will be in the

Introduction and/or on the ISO list of patent declarations received (see www.iso.org/patents) or the IEC

list of patent declarations received (see https://patents.iec.ch).

Any trade name used in this document is information given for the convenience of users and does not

constitute an endorsement.

For an explanation of the voluntary nature of standards, the meaning of ISO specific terms and

expressions related to conformity assessment, as well as information about ISO's adherence to

the World Trade Organization (WTO) principles in the Technical Barriers to Trade (TBT) see

www.iso.org/iso/foreword.html. In the IEC, see www.iec.ch/understanding­standards.

This document was prepared by Joint Technical Committee ISO/IEC JTC 1, Information technology.

A list of all parts in the ISO/IEC 3532 series can be found on the ISO and IEC websites.

Any feedback or questions on this document should be directed to the user’s national standards

body. A complete listing of these bodies can be found at www.iso.org/members.html and

www.iec.ch/national­committees.
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ISO/IEC FDIS 3532-1:2023(E)
Introduction

This document was developed in response to the need for customization of 3D scanning and 3D printing

technology within the medical industry, which can be achieved by taking full advantage of information

and communication technology (ICT).

This document addresses the overview of medical image processing and requirements for image-

based modelling. 3D printing technology has caused a revolution in health care delivery. New classes

of medical devices embody the true meaning of personalized medicine. Medical device designers and

practitioners are able to practically and efficiently create devices that were very difficult or impossible

to create before. In addition to using 3D printing technology to create standard medical devices with

features like intricate lattice structures, clinicians and engineers work in conjunction to produce what

are known as patient-specific devices or patient-matched devices. These are medical devices designed

to fit a specific patient’s anatomy, typically using medical imaging from that patient. Anatomically

matched devices have very complex geometrical contours and shapes. Several challenges exist in the

design process between the input data and the final device design. Most of these steps definitely depend

on software­based management of medical images.

Overall, the world revenue from 3D printing technology in the healthcare industry is expected to grow

exponentially, yet very few guides exist for 3D printing for medical practice. Medical images from the

human body are different from solid objects due to the non-geometric nature of the human body. To

perform 3D printing for medical practice, an accurate and consistent approach for image processing and

data creation from medical images is needed. Standardization for 3D printing processes in medicine

is urgently required for education, diagnosis, neurosurgical treatment, developing simulation models,

medical equipment (including surgical guides) and surgical implantable devices in the clinical fields.

Regulatory bodies from several countries (US, Repulic of Korea, etc.) have already published their

own guidelines for approval. However, those guidelines are not specifically designed for 3D printing

technology.

Applications of 3D printing in medicine are booming, such as surgical simulation models, surgical

guides, educational models, surgical implants, etc. Those which are manufactured by 3D printing

technology require patient- and/or procedure-specific data (e.g. planned surgical technique and others)

and medical image data acquisition processing. Most of the processing of medical images for 3D printing

medical devices is software-based. In order to accurately and consistently visualize human body

anatomy, appropriate software-based modelling for 3D printing is needed. This document provides

requirements of software-based medical image processing for the purpose of producing 3D models for

3D printing. Valuable information related to optimized medical image data for additive manufacturing

can be found in ISO/ASTM TR 52916.
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FINAL DRAFT INTERNATIONAL STANDARD ISO/IEC FDIS 3532-1:2023(E)
Information technology — Medical image-based modelling
for 3D printing —
Part 1:
General requirements
1 Scope

This document specifies the requirements for medical image-based modelling for 3D printing for

medical applications. It concerns accurate 3D data modelling in the medical field using medical image

data generated from computed tomography (CT) devices. It also specifies the principal considerations

for the general procedures of medical image-based modelling. It excludes soft tissue modelling from

magnetic resonance image (MRI).
2 Normative references

The following documents are referred to in the text in such a way that some or all of their content

constitutes requirements of this document. For dated references, only the edition cited applies. For

undated references, the latest edition of the referenced document (including any amendments) applies.

ISO/IEC 2382, Information technology — Vocabulary

ISO/ASTM 52900, Additive manufacturing — General principles — Fundamentals and Vocabulary

3 Terms, definitions and abbreviated terms

For the purposes of this document, the terms and definitions given in ISO/IEC 2382, ISO/ASTM 52900

and the following apply.

ISO and IEC maintain terminology databases for use in standardization at the following addresses:

— ISO Online browsing platform: available at https:// www .iso .org/ obp
— IEC Electropedia: available at https:// www .electropedia .org/
3.1 Terms and definitions
3.1.1
image acquisition

scanning of the structure of interest using computed tomography (CT), magnetic resonance imaging or

other three-dimensional imaging technology
3.1.2
slice distance
slice spacing

distance between the centre of the slices, which is calculated by the difference in the slice locations of

two adjacent slices
3.1.3
hard tissue

tissue which is mineralized and has a firm intercellular matrix (such as bone, tooth enamel, dentin and

cementum)
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ISO/IEC FDIS 3532-1:2023(E)
3.1.4
soft tissue

tissue that connects, supports or surrounds other structures and organs of the body, excluding hard

tissue (3.1.3)
3.1.5
solid organ

organ which has firm tissue consistency such as the heart, kidney, liver, lungs, pancreas, etc., excluding

hollow organs (such as the organs of the gastrointestinal tract) and tissue with liquid consistency (such

as blood)
3.1.6
pixel
picture element

smallest two-dimensional element of a display image that can be independently assigned attributes

such as color and intensity

[SOURCE: ISO/IEC 2382:2015, 2125999, modified — Notes to entry have been removed.]

3.1.7
voxel
volume element

smallest three-dimensional element in volume or volumetric (solid) modeling that can be independently

assigned attributes such as colour and intensity

[SOURCE: ISO/IEC 2382:2015, 2126000, modified — Notes to entry have been removed; "solid" has

been replaced by "volume or volumetric (solid)".]
3.1.8
vector data
vector image
vector model

digital description of 2D image or 3D model stored as a series of points and mathematical functions to

describe the geometric figure

[SOURCE: ISO 12651-1:2012, 4.139, modified — "image" has been replaced by "2D image or 3D model”.]

3.1.9
raster data
raster image
raster model
bitmap data
bitmap image
bitmap model

2D image or 3D model data formed by a set of picture elements (3.1.6) or volume elements (3.1.7)

arranged in a grid pattern
3.1.10
volume model
solid model

three-dimensional geometric model which deals with the solid characteristics of an object in order to

represent its internal structure as well as its external shapes

Note 1 to entry: See ISO/IEC 2382 for definitions of volume modeling and solid modeling.

Note 2 to entry: Volume model can be represented with raster model (3.1.9) or vector model (3.1.8).

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ISO/IEC FDIS 3532-1:2023(E)
3.1.11
surface model
boundary model
data set of a model which represents the surfaces of objects

Note 1 to entry: See ISO/IEC 2382 for definitions of surfacing and surface modeling.

3.1.12
facet model
faceted model
surface model (3.1.11) of which surfaces consist of group of polygons
Note 1 to entry: A triangle is widely used as a polygon.
3.1.13
segmentation
process of separating the objects of interest from their surroundings

Note 1 to entry: Segmentation can be applicable to 2D, 3D, raster or vector data (3.1.8).

3.1.14
3D visualization

presentation intended for human viewing of a scene on a flat display surface, using graphics techniques

to convey depth information and knowledge of the arrangement and shapes of the visualized scene in a

three­dimensional space

Note 1 to entry: The graphics techniques can include use of perspective, occlusion, stereoscopy, lighting and

environmental effects, and ability to navigate the viewpoint to alternate positions and orientations.

3.1.15
3D modelling

activity intended to create a digital representation of the form and arrangement of one or more 3D

objects in a three-dimensional space.

Note 1 to entry: 3D models can contain geometric information such as mesh vertices, appearance, lighting, and

animation information. The created representation is a prerequisite to creating a 3D visualization (3.1.14) of the

modelled objects.
3.1.16
maximum intensity projection
MIP

scientific visualization method for 3D data that projects in the visualization plane the voxels with

maximum intensity that fall in the way of parallel rays traced from the viewpoint to the plane of

projection.
3.1.17
minimum intensity projection
MinIP

data visualization method that enables detection of low-density structures in a given volume

Note 1 to entry: The algorithm uses all the data in a volume of interest to generate a single two-dimensional

image. In other words, it consists of projecting the voxel with the lowest attenuation value on every view

throughout the volume onto a 2D image.
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ISO/IEC FDIS 3532-1:2023(E)
3.1.18
Hounsfield value
Hounsfield unit

integer representing the intensity of the image at each image point [pixel (3.1.6)] which originates from

the x-ray scanning process and in turn represents the image intensity which in turn depends on the

density of the tissue at that location

Note 1 to entry: Hounsfield values rise monotonically with tissue density but are not linearly proportional to

density.

Note 2 to entry: The highest range of biological tissue Hounsfield values is for cortical bone, and they can go even

higher for image artefacts such as metallic implants, metallic sections of a hospital bed included in the image, etc.

3.1.19
multiplanar reformation
MPR

two-dimensional reformatted images that are reconstructed secondarily in arbitrary planes from the

stack of axial image data.

Note 1 to entry: Multiplanar reformation (MPR) allows images to be created from the original axial plane in

either the coronal, sagittal or oblique plane.
3.1.20
volume rendering

set of techniques used to display a 2D projection of a 3D discretely sampled data set, typically a 3D

scalar field
3.2 Abbreviated terms
2D two­dimensional
3D three­dimensional
AM additive manufacturing
AMF additive manufacturing file format
ANN artificial neural network
CAD computer aided design
CT computed tomography
DICOM digital imaging and communications in medicine
HU Hounsfield unit
PACS picture archiving communication system
QC quality control
ROI region of interest
STL stereolithography
SVM support vector machine
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ISO/IEC FDIS 3532-1:2023(E)
4 Overview of image processing for the medical industry
4.1 Process flow
4.1.1 3D printing process for medical applications

In general, the medical 3D printing processing flow can be divided into eight phases, as shown in

Figure 1.
1) Image acquisition phase

In the image acquisition phase, medical images are acquired from medical imaging devices such as CT.

2) Segmentation phase

In the segmentation phase, the acquired medical images are segmented to fit the design purpose and

are processed to be divided (segmented) to extract a subset that would represent the part(s) of the

anatomy under consideration.
3) 3D modelling phase

In the 3D modelling phase, the segmented data representing the human tissue is converted

(reconstructed) into a 3D model optimized for 3D printing.
4) 3D printing phase

In the 3D printing phase, 3D printing is performed using the 3D model designed. For this phase 3D

model is processed for 3D printing by slicing, assigning build parameters, being oriented and placed

within the build space, and can have support structures generated.
5) Post-processing phase

In the post-processing phase, the 3D printed part is post-processed to become fit for actual medical use.

6) Quality control (QC) phase

In the QC phase, the 3D printed part is finally verified to meet all requirements (user/design/quality/

risk).
7) Clinical application and review phase

In the clinical application and review phase, the 3D printed part is reviewed as applicable to clinical

application by the healthcare practitioner.
8) Post-market phase

In the post­marketing stage, the 3D printed part is managed based on the post­sale market management

policy according to product life cycle issues such as tracking management/recall.

4.1.2 Explanation of a typical use case (cranial implant case)

Computed tomography (CT) is a common imaging modality for medical applications. For instance, for

patients with a skull defect visiting a neurosurgical clinic, CT has been known as the gold standard

for investigating bone­related problems. Figure 1 shows that the CT images are initially transferred to

the PACS server in DICOM file format. DICOM images have been used to reconstruct 3D image through

segmentation and 3D modelling by certain software. This 3D modelled image is transformed and

exported to design software as a stereolithography (STL) file. After completion and confirmation of

3D cranial implant by designing software, a metal AM machine builds this implant as designed. Post-

processing such as heat treatment, machining, cleaning and sanding is performed. Reverse engineering

is performed to confirm the completeness of the implant before delivery by 3D scanning and matching

to the original digital blueprint. After QC, the implant is packed, sterilized and delivered. An operation

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ISO/IEC FDIS 3532-1:2023(E)

is performed to cover the defect with the 3D printed cranial implant. For this medical 3D printing

process, accuracy and reproducibility should be considered. The accuracy and reproducibility of the

parts (anatomical model, surgical guides, implant, etc.) from medical 3D printed parts are affected

by the sum of errors introduced in each step during data flow. These steps can be image acquisition,

segmentation and any subsequent post-processing of the segmented images. This document covers

processes 1, 2 and 3 as shown in Figure 1, ending with a 3D model of the relevant patient anatomy for

use in multiple other later processes. Activities related to items for processes 4 - 8 are addressed by

ISO/TC 261.

Figure 1 — Typical workflow of medical 3D printing (example: cranial implant case)

5 General requirements

To conform to this document, all of the following items shall be considered and relevant information

shall be documented.
— The medical image acquisition protocol by the CT scanner.
— The clinical purpose (bone/hard tissue) of image­based modelling.
— The segmentation method and associated parameters.
— The processes and parameters for 3D reconstruction.

Major parameters, settings and descriptions of methods used in the processes above shall be recorded.

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ISO/IEC FDIS 3532-1:2023(E)
6 Requirements of data processing
6.1 Medical image data flow

There are usually two medical image data flows involved in data processing: example flow and direct

flow. MIP, MinIP, MPRs and volume rendering are used before transporting the medical image to the

PACS server. Typically, DICOM files are used to make 3D images. However, many PACS companies

provide plugged­in 3D visualization software to reform raw data to 3D images and transport 3D images

directly to the PACS server as captured images. These 3D visualizations on the PACS server are 2D

projections of a 3D object and are not suitable for 3D modelling. The 2D printers for films prints out 2D

images (X ray radiograph, CT, MRI, etc.) or 3D-modelled captured images. See Figure 2.

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ISO/IEC FDIS 3532-1:2023(E)
Key
Example flow (dotted lines) Direct flow (solid lines)
1 scanned by device A scanned by device
2 convert to DICOM B 3D visualization
3 save to PACS server C save to PACS server
4 3D visualization D (transfer to STL)
5 transfer to STL or other file formats E directs to Figure 1
6 directs to Figure 1
Figure 2 — Data flow of medical images (Example)
6.2 Medical image acquisition/computed tomography scan

To make medical 3D models, sequential 2D images are necessary and should be acquired from sectional

images. Generally, 2D slice images are acquired from a CT scan of the patient's body at regular intervals

depending on the scanning needs. Each CT image set has its own strengths and weaknesses with

respect to the different objectives of the observation. Bones are typically clearly identified. Variabilities

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ISO/IEC FDIS 3532-1:2023(E)

of output depend on factors such as spatial resolution/voxel size of the images, which in turn depends

on the x-ray dosage, the quality of the scanned images, operator capability, and low and high resolution

on 2D to 3D conversion algorithms. Features smaller than 0,3 mm cannot be printed successfully with

some printing processes if smaller features are needed. This will require special considerations for

process selection and post­processing operations. Care should be taken in choosing the appropriate

3D printing technology and the part manufacturers should be requested to consider the required

resolutions.

For medical image acquisition, the typical slice distance of less than 1 mm is sufficient and the following

points shall be addressed.

— Required accuracy and clinical purposes shall be compatible. The CT scanning protocol shall be

specified beforehand to achieve the required accuracy of the final models.
— The highest accuracy or resolution of CT scan is not always necessary.

— The time between the acquisition of the patient images and the initiation of image-based modelling

shall be minimized.

Other factors which can influence the quality of the final scanned images are as follows.

— Possible patient motion during the scanning process and its implications on the imaging accuracy.

Even breathing can cause errors in scanning in cardiovascular applications, for example.

— The use of contrast media during the scanning process to highlight blood or other liquids through

various tracers.

— Any digital filtering techniques applied in the data processing at the scanning stage to produce the

DICOM data used later for segmentation and reconstruction.
6.3 Segmentation

Image segmentation divides the image into meaningful regions. Segmentation usually extracts one or

more subsets of the data from the whole dataset, such that each subset would represent an anatomical

part, or tissue of the same characteristics [(e.g. bone having high density versus soft tissue having lower

density so a simple threshold can be established based on Hounsfield unit (HU)] etc. Segmentation in

medical imaging is generally considered a difficult problem, mainly because of the sheer size of the

datasets coupled with the complexity and variability of the anatomic organs.

The situation is worsened by the shortcomings of imaging modalities (such as sampling artifacts,

noise, low contrast, etc.) that can cause the boundaries of anatomical structures to be indistinct and

disconnected. The segmentation process becomes challenging in the absence of clear distinction in the

characteristics desired, such as density ranges overlapping (e.g. very soft bone indistinguishable from

calcified cartilage), or blood vessel walls not sufficiently distinguishable from surrounding muscle

tissue, etc. The challenge is greater when the target tissue is complex (intermingled or touching) in

its location (e.g. small diameter nerves around the orbit and vessels and nerves through skull base

foramens, anterior of a distal femur in a highly arthritic patient appearing to be totally connected to

their patella, or small complex branched blood vessels.).

Thus, the main challenge of segmentation algorithms is to accurately extract the boundary of the solid

organ or region of interest (ROI) and separate it from the rest of the dataset. The notion of boundary

starts in a 2D context of an image slice. Boundaries from all images (slices) can help build whole models

after segmentation.

For the segmentation of bony structures from CT scans the following relevant segmentation

technologies can
...