1. Towards 3D gamma-ray imaging Enzo PARADISO EDUSAFE Final Review 20 June 2016

2. Overview Gamma camera prototype recap Panoramic gamma Imaging
Gamma sensor calibration
3-D Gamma imaging
Overview June 2016 – p. 2

3. EduPIX gamma camera Panoramic Gamma Imaging capabilities Embedded
Cross-Platform oriented
Scalable, loose coupling
Overview June 2016 – p. 3

4. Why an Embedded system?
Integration of proof of concept and the gamma camera prototype in a stand-alone embedded system, to increase reliability, scalability, improve performances, and reduce size
Why an embedded system – 20 June – p. 4
Odroid-XU3
NVIDIA Jetson TK1
Samsung Exynos5422 Cortex™-A15 2Ghz and Cortex™-A7 Octa core CPUs
Mali-T628 MP6(OpenGL ES 3.0/2.0/1.1 and OpenCL 1.1 Full profile)
2Gbyte LPDDR3 RAM PoP stacked
eMMC5.0 HS400 Flash Storage
2 x USB 3.0 Host, 1 x USB 2.0 Host
Gigabit Ethernet port
HDMI 1.4a for display
Size : 82 x 58 x 22 mm
Tegra K1 SOC
NVIDIA Kepler GPU with 192 CUDA cores
NVIDIA 4-Plus-1 quad-core ARM Cortex-A15 CPU
2 GB memory RAM
16 GB eMMC, SATA, SD/MMC
USB 3.0 & Micro USB-USB, RS232 serial port
HDMI 1.4
MiniPCI, GPIOs, and high-bandwidth camera interface

5. The Chosen One The ODROID-C2
The most robust board among the boards tested
Efficient Heat sink -> Low temperature -> No cooling fan
Adequate Performance combined with small size
Amlogic ARM® Cortex®-A53(ARMv8) 2Ghz quad core CPUs
Mali™-450 GPU (3 Pixel-processors + 2 Vertex shader processors)
2Gbyte DDR3 SDRAM
Gigabit Ethernet
40pin GPIOs + 7pin I2S
eMMC5.0 HS400 Flash Storage slot / UHS-1 SDR50 MicroSD Card slot
USB 2.0 Host x 4, USB OTG x 1 (power + data capable)
Infrared(IR) Receiver
The One - 20 June – p. 5

6. Cross Platform – EduPIX Front-end
HTML 5
JavaScript
WebGL/CSS 3D
To display panoramic and 3D images directly via the browser, without the need for any plugins
Cross platform – EduPIX Front end - 20 June – p. 6

7. Cross Platform – EduPIX Back-end
Python
Tornado web server
Scipy
PIL
Numpy
C++
OpenCV
ZeroMQ Distributed Messaging System
Scalability
Suitable for remote control and networking
Loose coupling
Efficiency
Linux operating system (obviously…)
Cross platform – EduPIX Back End - 20 June 2016 – p. 7

8. Outline Gamma camera prototype recap Panoramic gamma Imaging
Gamma sensor registration
3-D Gamma imaging
Outline - 20 June 2016 – p. 8

9. Panoramic Gamma Imaging - Visible Processing
Acquisition
Wave correction
Retrieve best frame aut.
Blend images
Registration data
Panoramic Gamma Imaging - Visible Processing overview - 20 June – p. 9
Optimize selected image
Final Pano
Warp images
Find features
Match features

10. Panoramic Gamma Imaging - Testing at ATLAS
Performing measurements with the gamma camera prototype at 2 meters from the ATLAS beam pipe
Estimated dose at camera location between 3 and 4 µSv/h, depending on the position and the orientation of the gamma camera
Panoramic gamma imaging – Testing - 20 June 2016 – p. 10

11. Panoramic Gamma Imaging - Testing at ATLAS
Gamma Panorama Image produced by the EduPIX gamma camera prototype projected in Spherical Mode (or Equirectangular).
For illustration purposes, the image is shown in black and white in a 360°x180° format with a width/height ratio of 360/180=2
Panoramic gamma imaging – Results - 20 June – p. 11

12. Outline Gamma camera prototype recap Panoramic gamma Imaging
Gamma sensor calibration
3-D Gamma imaging
Outline - 20 June 2016 – p. 12

13. Key Idea: Coded aperture imaging uses many pinholes
What is the relationships between pixel coordinates in the gamma image and the corresponding camera coordinates?
What are the position and orientation of the gamma camera relatively to a world co-ordinate system?
Key Idea - 20 June 2016 – p. 13

14. Key Idea: Coded aperture imaging uses many pinholes
What is the relationships between pixel coordinates in the gamma image and the corresponding camera coordinates?
What are the position and orientation of the gamma camera relatively to a world co-ordinate system?
We can calibrate the camera by analyzing the position between image points and the position of corresponding radioactive sources in the world. That is, we compute intrinsic and extrinsic parameters of the gamma camera
Gamma camera calibration - 20 June 2016 – p. 14
To calibrate a camera means to be able to relate its image points with the homogeneous world coordinates

15. Radioactive source distance retrieval
Once calibrated, we can combine the gamma camera with a depth sensor (multi-sensors calibration) in order to retrieve the distance of a source
Multi-camera calibration - 20 June 2016 – p. 15

16. Depth retrieval techniques overview
Several techniques to retrieve distance of points in a scene
Advantages and disadvantages for each method
Outline distance sensors - 20 June 2016 – p. 16

17. Depth sensor chosen for experiments
Asus Xtion Pro
Compact and light
Does not require power supply except USB
Depth map size (640 px x 480 px)
FOV: 58° H, 45° V, 70° D
Depth range: up to 5 meters
Accuracy of measurements: inversely proportional to distance, from 1 mm to 5 cm
The Asus Xtion Pro - 20 June 2016 – p. 17

18. Proposed Calibration Technique - Results
Examples and proof-of-concept - 20 June 2016 – p. 18
Mean reprojection Error per each gamma image, calculated using MATLAB and resulting from the proposed calibration technique

19. Proposed Calibration Technique - Results
Examples and proof-of-concept - 20 June 2016 – p. 19

20. Stereo Gamma Imaging Prototype
Examples and proof-of-concept - 20 June 2016 – p. 20

21. Proposed Calibration Technique - Results
Examples and proof-of-concept - 20 June 2016 – p. 21
Distance automatically retrieved of an 241Am source with 360 MBq estimated activity.

22. Proposed Calibration Technique - Results
Examples and proof-of-concept - 20 June 2016 – p. 22
Distance automatically retrieved of an 137Cs source with 263 MBq estimated activity.

23. Outline Gamma camera prototype recap Panoramic gamma Imaging
Gamma sensor calibration
3-D Gamma imaging
Outline - 20 June 2016 – p. 23

24. Challenges
Selection, testing and integration of appropriate methodology for data range estimation
Embedded / power efficient
Rapid
Acceptable tolerance
Retrieve distance automatically
Compute 3D position of radioactive sources
Design and development of appropriate software /hardware architecture solution for the prototype
3D gamma reconstruction:
Reconstruction of 3D model of the physical scene
Tracking in a continuous manner the 6 DoF pose of the sensor (location and orientation)
Volumetric integration of visible and gamma information
Challenges – 20 June 2016 – p. 24

25. 3D Gamma Imaging Algorithm - Main phases - 1
3D scan of the environment generating a point cloud of the geometric entities within the scene
Localize and process radioactive hotspots in 2D using coded-aperture imaging techniques from one or more different perspectives
3D Gamma Imaging - Main phases – 20 June – p. 25
Example of 3-D point cloud data visualization – Laboratory in Canberra Montigny-le-Bretonneux

26. 3D Gamma Imaging Algorithm - Main phases - 2
6 DoF pose tracking of the camera of the sensor (location and orientation)
Alignment (in this phase the gamma camera location and orientation are estimated)
Occluding material/object
3D Gamma Imaging - Main phases – 20 June 2016 – p. 26
Measurement
from Pose1
Occluded radioactive material/object

27. 3D Gamma Imaging Algorithm - Main phases - 3
Tracking of the 6 DoF pose of the sensor (location and orientation)
Alignment (in this phase the gamma camera location and orientation are estimated)
Occluding material/object
3D Gamma Imaging - Main phases – 20 June 2016 – p. 27
Measurement
from Pose2
Measurement
from Pose1
Occluded radioactive material/object

28. 3D Gamma Imaging Algorithm - Main phases - 4
Add depth information to the hotspot profile
Voxelized model
3D Gamma Imaging - Main phases – 20 June 2016 – p. 28
Dynamic voxelization for 3D imaging

29. 3D Gamma Imaging Algorithm - Main phases - 5
Volumetric integration: the 3D volume is dynamically merged with the textured 3D mesh and the information of the radioactive source, if any
Visualization
Constrain the 3D gamma-ray image space to the surfaces of physical objects.
3D Gamma Imaging - Main phases – 20 June 2016 – p. 29

30. Thank you!