Here's a photograph of the status of our project: what we have done in sw and what we're gonna do in hw!

2. 2

3. ❏ Segmentation
implementation
(stable version)
❏ Segmentation
implementation
(optimized version)
❏ Sympthom
implementation
(stable version)
Translation
3

4. ❏ Segmentation
implementation
(stable version)
❏ Segmentation
implementation
(optimized version)
❏ Sympthom
implementation
(stable version)
Translation
● easy to learn
● filters already
implemented
● mostly used
● suitable for image
processing
4

5. ❏ Segmentation
implementation
(stable version)
❏ Segmentation
implementation
(optimized version)
❏ Sympthom
implementation
(stable version)
Translation
● easy to learn
● filters already
implemented
● mostly used
● suitable for image
processing
● the one that can
be translated in
HW language
● basic enough
● with no external
libriaries
5

6. ❏ Segmentation
implementation
(stable version)
❏ Segmentation
implementation
(optimized version)
❏ Sympthom
implementation
(stable version)
Translation
● easy to learn
● filters already
implemented
● mostly used
● suitable for image
processing
● the one that can
be translated in
HW language
● basic enough
● with no external
libriaries
● translates thanks
to Vivado HLS
● suitable for hw
synthesis
● mostly used
6

7. PYTHON PYTHON PYTHON
➔
➔
➔
➔
➔
➔
➔
➔
7

8. Detect vessels
Find vessels structure
Dilate/Erode
Supporting function
8

9. ●
●
●
●
9

10. ●
●
●
10

11. ●
●
●

12. ●
●
●
12

13. Vessels Image Supporting matrix
●
13

14. Supporting matrix
2
3
4 3 3
Supporting matrix
0 0 0 0 0 0
0 1 1 0 0 0
0 0 1 0 0
0 0 0 0 0 0
0 0 0 0 0
0 0 0
Vessels Image
●
●
14

15. 4
Supporting matrix
2
3
3 3
Supporting matrix
0 0 0 0 0 0
0 1 1 0 0 0
0 0 1 0 0
0 0 0 0 0 0
0 0 0 0 0
0 0 0
Vessels Image
●
●
●
15

16. 0
4
Supporting matrix
3
3 3
Supporting matrix
0 0 0 0 0 0
0 1 1 0 0 0
0 0 1 0 0
0 0 0 0 0 0
0 0 0 0 0
0 0 0
Vessels Image
●
●
●
●
16

17. ●
●
●
●
17

18. ●
●
●
18

19. Manual - Ac = 100% Our implementation - Ac = 93%
19

20. 20

21. 21

22. Facebook https://www.facebook.com/beye.project/
Twitter https://twitter.com/BEye_NECSTLab
Politecnico di Milano, NECST lab for Xilinx Open Hardware Contest 2016 #XOHW16