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Source: Pattern Recognition, 37(5), P , 2004

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Presentation on theme: "Source: Pattern Recognition, 37(5), P , 2004"— Presentation transcript:

1 Elastic registration of electrophoresis images using intensity information and point landmarks
Source: Pattern Recognition, 37(5), P , 2004 Authors: K. Rohr, P. Cathier, S. Worz Speaker: Chia-Chun Wu (吳佳駿) Date: 2005/02/24

2 Outline Introduction Proposed method Experimental results Conclusions

3 Fig. 2. Original electrophoresis image pair and
Introduction Fig. 2. Original electrophoresis image pair and marked landmarks.

4 Proposed method Extraction of point landmarks
Elastic image registration

5 Extraction of point landmarks
A model fitting approach 2D Gaussian function

6 Extraction of point landmarks
Fig. 1a. Example spot from electrophoresis image: intensities (left), 3D plots of the intensities (middle), and 3D plots of the fitted models (right).

7 Extraction of point landmarks
Fig. 1b. Example spot from electrophoresis image: intensities (left), 3D plots of the intensities (middle), and 3D plots of the fitted models (right).

8 Extraction of point landmarks
Fig. 1c. Example spot from electrophoresis image: intensities (left), 3D plots of the intensities (middle), and 3D plots of the fitted models (right).

9 Extraction of point landmarks
ơx, ơy: standard deviations a0: background intensity a1: peak intensity

10 Extraction of point landmarks
Parametric intensity model: Minimize Let

11 Extraction of point landmarks

12 Extraction of point landmarks

13 Elastic image registration
Registration algorithm: PASTAGA( PASha Treating Additional Geometric Attributes) algorithm[17][29] Using prominent point landmarks as geometric features

14 Experimental results Parameter settings Image size: 1024×1024 pixels
Landmark extraction: 3~10 points Size of ROI: 21×21 or 31×31 pixels

15 Experimental results (1)
Fig. 2. Original electrophoresis image pair (easy example) and marked landmarks.

16 Experimental results (1)
Fig. 5. Deformed grid according to the registration result using landmarks of the images in Fig. 2.

17 Experimental results (1)
Fig. 3. Registration result of the images in Fig. 2 (contour overlay): without landmarks (left) and using landmarks (right).

18 Experimental results (1)
Fig. 4. Enlarged sections of Fig. 3.

19 Experimental results (2)
Fig. 6. Original electrophoresis image pair (medium example) and marked landmarks.

20 Experimental results (2)
Fig. 7. Registration result of the images in Fig. 6 (contour overlay): without landmarks (left) and using landmarks (right).

21 Experimental results (2)
Fig. 8. Enlarged sections of Fig. 7.

22 Experimental results (3)
Fig. 9. Original electrophoresis image pair (difficult example) and marked landmarks.

23 Experimental results (3)
Fig. 10. Registration result of the images in Fig. 9 (contour overlay): without landmarks (left) and using landmarks (right).

24 Experimental results (3)
Fig. 11. Enlarged sections of Fig. 10.

25 Experimental results (4)
Fig. 12. Original electrophoresis image pair (Compugen example) and marked landmarks.

26 Experimental results (4)
Fig. 13. Registration result of the images in Fig. 12 (contour overlay): without landmarks (left) and using landmarks (right).

27 Experimental results (4)
Fig. 14. Enlarged sections of Fig. 13.

28 Experimental results

29 Experimental results

30 Conclusions An approach for elastic registration of 2D gel electrophoresis image using intensity and landmark information. Improve registration accuracy for images of easy and medium complexity.


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