Dataset Tracht6A
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Dataset Tracht6A Spines Nonspine s 1 Manually Scored Spines
description
Dataset Tracht6A. Manually Scored Spines. Spines Nonspines. Dataset Tracht6A. Principal factors in the algorithm. Missed spines False spines. MDL algorithm. Dataset Tracht6A. Principal factors in the algorithm. Morphology method without MDL. Missed spines False spines. - PowerPoint PPT Presentation
Transcript of Dataset Tracht6A
Dataset Tracht6A
Spines Nonspines
1
ManuallyScored Spines
Dataset Tracht6A
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
0.2
IW-MST edge range
8
Graph prune size 4
Graph morph strength
70
MDL weight factorα
0.70
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
2
Dataset Tracht6A
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.15
High curvature threshold
1.5
IW-MST edge range
10
Graph prune size 4
Graph morph strength
70
3
Dataset Tracht7A
Spines Nonspines
4
ManuallyScored Spines
Dataset Tracht7A
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
0.1
IW-MST edge range
8
Graph prune size 4
Graph morph strength
70
MDL weight factorα
0.70
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
5
Dataset Tracht7A
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
0.1
IW-MST edge range
8
Graph prune size 4
Graph morph strength
50
6
Dataset Tracht8A
Spines Nonspines
7
ManuallyScored Spines
Dataset Tracht8A
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
0.2
IW-MST edge range
8
Graph prune size 4
Graph morph strength
50
MDL weight factorα
0.70
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
8
Dataset Tracht8A
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
-0.3
IW-MST edge range
8
Graph prune size 4
Graph morph strength
50
9
Dataset Tracht11A
Spines Nonspines
10
ManuallyScored Spines
Dataset Tracht11A
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
0.4
IW-MST edge range
12
Graph prune size 4
Graph morph strength
50
MDL weight factorα
0.70
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
11
Dataset Tracht11A
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.14
High curvature threshold
0.2
IW-MST edge range
8
Graph prune size 4
Graph morph strength
50
12
Dataset Tracht14A
Spines Nonspines
13
ManuallyScored Spines
Dataset Tracht14A
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.10
High curvature threshold
0.6
IW-MST edge range
15
Graph prune size 4
Graph morph strength
50
MDL weight factorα
0.7
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
14
Dataset Tracht14A
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.1
High curvature threshold
0
IW-MST edge range
8
Graph prune size 2
Graph morph strength
50
15
Dataset time330 Spines Nonspines
ManuallyScored Spines
16
Dataset time330
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
10
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.12
High curvature threshold
0.2
IW-MST edge range
5
Graph prune size 4
Graph morph strength
50
MDL weight factorα
0.95
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
17
Dataset time330
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
1000
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.12
High curvature threshold
0.2
IW-MST edge range
5
Graph prune size 4
Graph morph strength
50
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Dataset MBFsp5
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.05
High curvature threshold
0
IW-MST edge range
8
Graph prune size 4
Graph morph strength
50
MDL weight factorα
0.95
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
19
Dataset MBFsp5
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.04
High curvature threshold
0.2
IW-MST edge range
10
Graph prune size 10
Graph morph strength
50
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Dataset MBFsp6
Principal factors in the algorithm
Parameters Values
Intensity threshold 2
Connected components size
10
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.08
High curvature threshold
0.2
IW-MST edge range
5
Graph prune size 4
Graph morph strength
70
MDL weight factorα
0.95
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
21
Dataset MBFsp6
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 7
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.06
High curvature threshold
0.2
IW-MST edge range
10
Graph prune size 10
Graph morph strength
50
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Dataset MBFsp8
Principal factors in the algorithm
Parameters Values
Intensity threshold 7
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.06
High curvature threshold
10
IW-MST edge range
30
Graph prune size 4
Graph morph strength
30
MDL weight factorα
0.95
Extra spine offset 1.5
MDL algorithm
Missed spinesFalse spines
23
Dataset MBFsp8
Morphology method
without MDL
Missed spinesFalse spines
Principal factors in the algorithm
Parameters Values
Intensity threshold 7
Connected components size
100
Anisotropic Diff k 800
Anisotropic Diff t 2
Critical pts vector magnitude
0.06
High curvature threshold
10
IW-MST edge range
30
Graph prune size 10
Graph morph strength
30
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