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Doing Ontology Over Images

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Title: Doing Ontology Over Images


1
Doing Ontology Over Images
  • Barry Smith

2
What ontologies are for
3
what molecular function ?
what disease process ?
need for semantic annotation of data
4
need for semantic annotation of data
through labels (nouns, noun phrases) which are
algorithmically processable
5
natural language labels
to make the data cognitively accessible to human
beings
6
compare legends for maps
compare legends for maps
7
compare legends for cartoons
8
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9
ontologies are legends for data
10
ontologies are legends for images
11
what lesion ?
what brain function ?
12
ontologies are legends for mathematical equations
xi vector of measurements of gene i k the
state of the gene ( as on or off) ?i set of
parameters of the Gaussian model ... ...
13
The OBO Foundry Idea
GlyProt
MouseEcotope
sphingolipid transporter activity
DiabetInGene
GluChem
14
annotation using common ontologies yields
integration of databases
GlyProt
MouseEcotope
Holliday junction helicase complex
DiabetInGene
GluChem
15
annotation using common ontologies can yield
integration of image data
16
annotation using common ontologies can support
comparison of image data
17
truth
18
simple representations can be true
19
there are true cartoons
20
a cartoon can be a veridical representation of
reality
21
Cartographic Projection
22
maps may be correct by reflecting topology,
rather than geometry
23
an image can be a veridical representation of
reality
a fully labeled image can be an even more
veridical representation of reality
24
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26
cartoons, like maps, always have a certain
threshold of granularity
27
grain resolution
28
grain resolution serves cognitive accessibility
we transform true imagesinto true cartoons
29
there are also true cartoon sequences
30
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31
Pathway diagrams are annotated dynamic cartoons
32
pathways can be represented at different levels
of granularity
33
the jaw
34
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35
Joint capsule
Netter
36
Mandible and condyle movement
37
Condyle position in fossa wrt location of disc
38
TMJ in jaw open and closed positions
39
Holes and Parts
  • Parts
  • 1 head of condyle F
  • 2 neck of condyle F
  • 3 disc B
  • 4 retrodiscal tissue B
  • 7 articular eminence F
  • 8 zygomatic arch F
  • 10 upper head of lateral pterygoid muscle F
  • 11 lower head of lateral pterygoid muscle F
  • Holes
  • 5 lower joint compartment B
  •  6 upper joint compartment B

40
Temporomandibular Joint (TMJ)
ANTERIOR
from Thomas Bittner and Louis Goldberg, KR-MED
2006
41
adjacency relations
Connectedness adjacency graph
42
Frames of reference
F
C
E
Rigid do not change shape (bones)
B
D
A
The extension of the axis of the
condyle intersects the fossa in region D
43
instances vs. types
44
two kinds of annotations
45
names of instances
46
names of types
47
pathway maps are representations of complexes of
types
48
molecular images and radiographic images are
representations of instances
49
MIAKT system
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Patient 47920
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Mammography 31667
57
Medical-Image 44922
Mammography 31667
58
Patient 47920
Medical-Image 44922
Breast 1388
MRI-Exam 32388
Mammography 31667
59
SNAP and SPAN in brain imaging
  • SNAP CT Computer TomographyPET Positron
    emission tomographySPECT Single Photon Emission
    CTMRTfMRTMRSSPANEKP event correlate
    potentialquantitative electroencephalographyqEEG

60
  • canonicity !
  • fiatness !
  • granularity !

61
  • digital representations of analogue reality
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