ISO/IEC 3532-1:2023 情報技術 — 3D プリンティング用の医用画像ベースのモデリング — Part 1: 一般要件 | ページ 6

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)

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) modelling 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[SOURCE:ISO/IEC 2382:2015, 2126000, modified — Notes to entry have been removed;"solid" has been replaced by"volume or volumetric (solid)".]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[SOURCE:ISO 12651-1:2012, 4.139, modified —"image" has been replaced by"2D image or 3D model”.]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 modelling and solid modelling.

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

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 modelling.

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 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 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 and with maximum intensity, the voxels 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 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 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