Performed by: Oleg GolanMentor: Yoav Kimchy, Ph.DInstructor: Mony Orbach

Bi-Semesterial, Spring 2014, part A

Adaptive filterFor noise cancellation of ELS

Agenda

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1. Introduction

2. Problem description

3. Project goal

4. Solution presentation

5. ANN based adaptive filter simulator

6. Testing methods

7. Gant chart

8. Q&A

First imaging capsule for Colorectal Cancer screening

No bowel cleansing required

Designed for increased compliance

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Check-Cap - creating a new standard of colon 3D imagery

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

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B a c k - S c a tt e r i n g X - r a y F l u o r e s c e n c e

Check-Cap Imaging Technology

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Reconstruction with dimensions

ELS Tracking Capture

ELS – Electromagnetic Localization System Movement/Position Tracking VS Reconstruction

Capsule and receiver communication

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3D-Accelerometer

3D-Magnetometer

Magnetic, solid freq. burst

RF link

Air coil

Relative orientation

Distance and direction

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Noiseonamplitudes

The problem ELS magnetic burst structure

Noiseoncapsuleposition

Noiseoncapsulevelocity

False-positivescan activations

Capsule batterydrained too fast

Short bursts – signal energy not sufficient for conventional FIR/IIR filters to converge.

Far locations – low SNR (magnetic dipole field ~ 1/r³).

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The goal Improve amplitudes SNR

• Fast convergence noise reduction

• Expand capsule detection area with no modifications in the capsule design.

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121 – 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

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Adaptive filter Principle

∑

Filter ň

s + n

Reference inputn₀

+

-

š = s + (n – ň)

Reference output

Inputs - 1) Noisy signal (s + n)

2) Correlated noise (n₀)

Output – Adapted noise (ň)

2 22

2

2

2

s n n s s n n n n

s s n n

2n n

2s

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The simulator ANN in a nutshell

LABVIEW front panel with MATLAB in background

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Testing methods SNR improvement vs. time consumption

1. Time consumption

2. SNR improvement

3. Same parameters, different data

4. Different parameters, same data

5. Recorded data

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Gant chart

ID Task Name Start Finish Duration 2014 2014 2014

29/68/6 6/722/615/625/5 1/6

1 7d30/05/201422/05/2014Finish simulator implementation

2 14d19/06/201402/06/2014Analyze options for ANN implementation, select best

3 7d30/06/201420/06/2014Implement adaptive filter into ELS project(reuse simulator vi)

4 7d09/07/201401/07/2014Recorded data processing, results and conclusions

Q & A

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T H A N K YO U

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