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Dataset Tracht6A Spines Nonspines 1 Manually Scored Spines.

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Presentation on theme: "Dataset Tracht6A Spines Nonspines 1 Manually Scored Spines."— Presentation transcript:

1 Dataset Tracht6A Spines Nonspines 1 Manually Scored Spines

2 Dataset Tracht6A Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold 0.2 IW-MST edge range 8 Graph prune size4 Graph morph strength 70 MDL weight factorα 0.70 Extra spine offset1.5 MDL algorithm Missed spines False spines 2

3 Dataset Tracht6A Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.15 High curvature threshold 1.5 IW-MST edge range 10 Graph prune size4 Graph morph strength 70 3

4 Dataset Tracht7A Spines Nonspines 4 Manually Scored Spines

5 Dataset Tracht7A Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold 0.1 IW-MST edge range 8 Graph prune size4 Graph morph strength 70 MDL weight factorα 0.70 Extra spine offset1.5 MDL algorithm Missed spines False spines 5

6 Dataset Tracht7A Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold 0.1 IW-MST edge range 8 Graph prune size4 Graph morph strength 50 6

7 Dataset Tracht8A Spines Nonspines 7 Manually Scored Spines

8 Dataset Tracht8A Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold 0.2 IW-MST edge range 8 Graph prune size4 Graph morph strength 50 MDL weight factorα 0.70 Extra spine offset1.5 MDL algorithm Missed spines False spines 8

9 Dataset Tracht8A Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold -0.3 IW-MST edge range 8 Graph prune size4 Graph morph strength 50 9

10 Dataset Tracht11A Spines Nonspines 10 Manually Scored Spines

11 Dataset Tracht11A Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold 0.4 IW-MST edge range 12 Graph prune size4 Graph morph strength 50 MDL weight factorα 0.70 Extra spine offset1.5 MDL algorithm Missed spines False spines 11

12 Dataset Tracht11A Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.14 High curvature threshold 0.2 IW-MST edge range 8 Graph prune size4 Graph morph strength 50 12

13 Dataset Tracht14A Spines Nonspines 13 Manually Scored Spines

14 Dataset Tracht14A Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.10 High curvature threshold 0.6 IW-MST edge range 15 Graph prune size4 Graph morph strength 50 MDL weight factorα 0.7 Extra spine offset1.5 MDL algorithm Missed spines False spines 14

15 Dataset Tracht14A Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.1 High curvature threshold 0 IW-MST edge range 8 Graph prune size2 Graph morph strength 50 15

16 Dataset time330 Spines Nonspines Manually Scored Spines 16

17 Dataset time330 Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 10 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.12 High curvature threshold 0.2 IW-MST edge range 5 Graph prune size4 Graph morph strength 50 MDL weight factorα 0.95 Extra spine offset1.5 MDL algorithm Missed spines False spines 17

18 Dataset time330 Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 1000 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.12 High curvature threshold 0.2 IW-MST edge range 5 Graph prune size4 Graph morph strength 50 18

19 Dataset MBFsp5 Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.05 High curvature threshold 0 IW-MST edge range 8 Graph prune size4 Graph morph strength 50 MDL weight factorα 0.95 Extra spine offset1.5 MDL algorithm Missed spines False spines 19

20 Dataset MBFsp5 Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.04 High curvature threshold 0.2 IW-MST edge range 10 Graph prune size10 Graph morph strength 50 20

21 Dataset MBFsp6 Principal factors in the algorithm ParametersValues Intensity threshold2 Connected components size 10 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.08 High curvature threshold 0.2 IW-MST edge range 5 Graph prune size4 Graph morph strength 70 MDL weight factorα 0.95 Extra spine offset1.5 MDL algorithm Missed spines False spines 21

22 Dataset MBFsp6 Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold7 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.06 High curvature threshold 0.2 IW-MST edge range 10 Graph prune size10 Graph morph strength 50 22

23 Dataset MBFsp8 Principal factors in the algorithm ParametersValues Intensity threshold7 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.06 High curvature threshold 10 IW-MST edge range 30 Graph prune size4 Graph morph strength 30 MDL weight factorα 0.95 Extra spine offset1.5 MDL algorithm Missed spines False spines 23

24 Dataset MBFsp8 Morphology method without MDL Missed spines False spines Principal factors in the algorithm ParametersValues Intensity threshold7 Connected components size 100 Anisotropic Diff k800 Anisotropic Diff t2 Critical pts vector magnitude 0.06 High curvature threshold 10 IW-MST edge range 30 Graph prune size10 Graph morph strength 30 24


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