1. Performed by: Oleg Golan Mentor: Yoav Kimchy, Ph.D Instructor: Mony Orbach Bi-Semesterial, Spring 2014, part A Adaptive filter For noise cancellation of ELS

2. Agenda 2 1.Introduction 2.Problem description 3.Project goal 4.Solution presentation 5.ANN based adaptive filter simulator 6.Testing methods 7.Results 8.Q&A

3. First imaging capsule for Colorectal Cancer screening No bowel cleansing required Designed for increased compliance 3 Check-Cap - creating a new standard of colon 3D imagery

4. Compton backscattered flux of photons detected by the capsule are attenuated by the colon contents in direct proportion to their distance traveled in the colon contents, as some of the photons are absorbed by the contrast agent The x-ray Florescence flux detected by the capsule's detectors depends monotonically on the distance traveled in the colon contents mixed with the contrast agent 4 Back-Scattering X-ray Fluorescence Check-Cap Imaging Technology

5. 5 Reconstruction with dimensions ELS Tracking Capture ELS – Electromagnetic Localization System Movement/Position Tracking VS Reconstruction

6. Capsule and receiver communication 6 3D-Accelerometer 3D-Magnetometer Magnetic, solid freq. burst RF link Air coil Relative orientation Distance and direction

7. 7 Noise on amplitudes The problem ELS magnetic burst structure Noise on capsule position Noise on capsule velocity False-positive scan activations Capsule battery drained too fast Short bursts – signal energy not sufficient for conventional FIR/IIR filters to converge. Far locations – low SNR (magnetic dipole field ~ 1/r ³ ).

8. 8 The goal Improve amplitudes SNR Fast convergence noise reduction Expand capsule detection area with no modifications in the capsule design.

9. 9 1 2 1 – Signal sampling window 2 – Noise sampling window The solution Adaptive noise cancellation Assumptions Simple correlation of noise signals in both windows No correlation between the noise and the desired signal Expectation 0 of the desired signal

10. 10 Adaptive filter Principle Inputs - 1) Noisy signal (s + n) 2) Correlated noise (n ₀) Output – Adapted noise ( ň)

11. 11 The simulator ANN in a nutshell

12. 12 Testing methods SNR improvement vs. time consumption

13. 13 Results ADALINE MATLAB vs. LabVIEW ADALINE MATLAB output ADALINE LabVIEW output

14. 14 Results FFBP simplifications LESS IS MORE LESS IS MORE

15. 15 Results ADALINE vs. FFBP ADALINE outputFFBP output

16. Q&A 16

17. THANK YOU 17