Relations in Anatomy and Image Ontologies Dirk Marwede Institute for Formal Ontology and Medical Information Science, Saarland University, Saarbruecken,

Relations in Anatomy and Image Ontologies

Dirk Marwede

Institute for Formal Ontology and Medical Information Science, Saarland University, Saarbruecken, Germany

Department of Diagnostic Radiology, Leipzig University, Germany

Overview

• OBO relation ontology

• Anatomical Entities (Foundational Model of Anatomy, FMA)

– Relations in Anatomy Ontology

• Diagnostic Domain of Medial Imaging

– Image Entity Types

– Relations between Image Entity Types

– Building an Imaging Ontology (RadiO)

OBO relation ontology• Three types of binary relations

– < class, class >: e.g. is_a lung is_a lobular organ

– < instance, class >: instance_ofThis particular „lung“ instance_of class lung

– < instance, instance >: instance-level relation, e.g. part_ofThis particular instance of „right lower lobe of lung“ part_of this

particular instance of „right lung“

• Relations between classes represent what is general in reality. – class level:

• lung is_a lobular organ

– instance level: • this particular instance of lung is_a particular instance of lobular organ

Anatomical Ontologies (FMA)

• Class level-relations

– Structural Relationships between Anatomical Entities

• Boundary (bounded_by)

• Partonomy (part_of, regional_part_of, constitutional_part_of,…)

• Spatial Association

– Location (located_in, contained_in, adjecent_to)– Orientation (coordinate, laterality)– Connectivity (continuous_with, attached_to)

– Properties of Anatomical Entities:

• Dimension • Physical Properties

Canonical Anatomical Entity - Lung

Image Ontologies

• Medical Imaging is concerned with diagnosing diseases.

• How we come from an image to a diagnosis?

– What kind of entities exist on the image and how do they relate to each other ?

• Image Entity Types

– Anatomical Image Entities

– Pathological Image Entities

– Image Features

dependent entities

Imaging body entites

Image Entity Types – Anatomical Image Entities

Image Entity Types – Pathological Image Entity

• Which diseases can be inferred from images?

• What kind of image features do diseases have?

• Does a disease have in any case identical image features?

• If not, what are criteria which give evidence for a disease?

Pathological Image Entities

Features

Class-Level Relations between Image Entity Types

• C image_of C1 – basic relation holding between two continuants. – C is an anatomical or pathological image entity, C1 is an anatomical or

pathological entity.

• C has_feature C1 – a property relation holding between two continuants. – C is an anatomical or pathological image entity, C1 is a feature attribute.

• C has_location C1 – basic location relation holding between two continuants. – C is a visual feature or pathological image entity and C1 is an anatomical

image entity

Class-level relations between Image Entity Types and the FMA

has_feature

Anatomical Image Entityimage_of

Anatomical Entity (FMA)

Pathological Image EntityFeature

has_location

has_feature

has_location

Subrelations of has_feature Relations to annotate properties to anatomical and pathological image entities

Visual features

Morphology featuresc has_shape c1 at time of examination.

Adrenal gland [Anatomic Image Entity] has_shape round [Attribute:Shape] at time of examination

c has_size c1 at time of examination.T1 vertebral body [Anatomical Image Entity] has_size decreased in height [Attribute:Size] at time of examination

c has_composition c1 at time of examination.Tumor [Pathological Image Entity] has_composition cystic [Attribute:Composition] at time of examination

Signal features

c has_density c1 at time of examination.Liver [Anatomical Image Entity] has_density hypodense [Attribute:Density] at time of examination (or contrast phase).

General features

c has_amount c1 at time of examination.Pulmonary nodule [Pathological Image Entity] has_amount multiple [Attribute:Amount] at time of examination.

Use of Relations in Medical Imaging [Pathological Image Entity] has_feature [GeneralFeature]

Pulmonary embolism has_timing acute

[Pathological Image Entity] has_location [Anatomical Image Entity]has_feature [MorphologyFeature]

Mass has_location upper right lobe of right lunghas_margin spiculatedhas_shape roundhas_composition solid

evidence for malignant neoplasm

[Anatomical Image Entity] has_feature [MorphologyFeature]

Thyroid gland has_size enlarged

[Anatomical Image Entity] has_feature [MorphologyFeature][Pathological Image Entity] has_location [Anatomical Image Entity]

Hilar lymph node has_composition calcifiedGranuloma has_location upper lobe of left lung

evidence for tuberculosis has_timing old

Disease Ontology

Imaging Ontology

Imaging Ontology

Imaging Ontology ?

Disease Ontology

Conclusions• Entities of two domains

– Body Entities– Image Entities (dependent entities)

• Construction of an Imaging Ontology

– Image Entity Types

• Anatomical Image entities • Pathological Image Entities • Features

– Class level relations between Image Entity Types (and the FMA)

• Application Ontology (RadiO) for Diagnostic Domain

– Annotating image features to Anatomical and Pathological Image entities.

– Criteria for Pathological Image Entities: Tracking the use of relations between image entity types to discriminate image features of diseases.

• Separating/linking of an Imaging Ontology from/to other Ontologies of Diseases/Diagnosis.

Thank you!

Matthew FieldingBarry SmithDaniel Rubin

RadLex Committee