Cancer Node Detection Using Ultrasonic MIMO RadarAKHILESH MISHRA

OutlineIntroductionSystem Model Simulation RADAR Detection ProblemResults References

Introduction Disadvantages of Existing techniques for cancer detection

X ray Mammography -> Chances high for false negative

Microwave Imaging -> Provides low spatial resolution

MRI -> Painful and long

Alternative is to use Ultrasound Waves in MIMO(Multiple Input Multiple Output) RADAR.

Why we use that ??

High Resolution, No radiation exposure, Safe

System Model

[1]-Breast Cancer Nodes Detection Using Ultrasonic Microscale Subarrayed MIMO RADAR- A. Taparugssanagorn, S. Siwamaogasatham, C.Raez

Frequency used 10- 15MHz Nt transmit Antennas, Nr receive Antennas both divided in Ns

subarrays Matched Filtering for signal waveform extraction RCS is now a random variable Multiple independent measurements – Better detection

performance and better spatial resolution Relative permittivities of Normal tissue and Tumor tissue [2]

Statistical behavior of received signal [3]Phase is uniformly distributed Magnitude modelled as Nakagami-distribution

Simulations (Single Input Multiple Output)

RADAR Parameters :

Center frequency 15 MHz

Pulse Duration 20s

Transmitted wave Chrip with 5 MHz BW

Transmit window Hanning

Sampling frequency 80MHz

Receive Antenna Elements 6, Uniform Linear Array

Speed 1500m/s

Targets 3 point targets at 0 degrees, -60 degrees and 30 degrees

Fig 3. Frequency Spectrum of Transmitted Chirp Fig 4. Radiation Pattern of Receive Antenna

Fig 5. Received Signal Echoes from 3 point targets Fig 6. Pulse Compressed Received Signal

Fig 7. MUSIC Periodogram to estimate Angle of Arrival

Angle of Arrival Estimation using MUSIC Algorithm

Fig 8. MVDR Radiation Pattern for = 0 degree Fig 9. Clutter removed from signal

Case 1: Assuming signal at 0 degree is our signal of interest

Fig 10. MVDR Radiation Pattern for = -60 degree

Case 2: Assuming signal at -60 degree is our signal of interest

Fig 11. Clutter Removed from the signal

Radar Detection Use the MAP decision rule for detection of target.

Maximum Likelihood estimate of angle of target and its amplitude

Results

Table 1,2 & 3- [1]-Breast Cancer Nodes Detection Using Ultrasonic Microscale Subarrayed MIMO RADAR- A. Taparugssanagorn, S. Siwamaogasatham, C.Raez

References 1. A. Taparugssanagorn, S. Siwamaogasatham, C.Raez -”Breast Cancer Nodes Detection Using Ultrasonic Microscale Subarrayed MIMO RADAR”, Advances in

Bioinformatics Volume 2014, Article ID 797013, 8 pages

2. S. K. Davis, H. Tandradinata, S. C. Hagness, and B. D. van Veen, “Ultrawideband microwave breast cancer detection: a detection-theoretic approach using the generalized likelihood ratio test,” IEEE Transactions on Biomedical Engineering, vol. 52,no. 7, pp. 1237–1250, 2005.

3. N. Bahbah, H. Djelouah, and A. Bouakaz, “Use of Nakagami statisticalmodel in ultrasonic tissue mimicking phantoms characterization,”in Proceedings of the 24th International Conference on Microelectronics (ICM ’12), December 2012.

4. E. Brookner, “Phase arrays around the world progress and future trends,” in Proceedings of the IEEE International SymposiumPhased Array Systems and Technology, pp. 1–8, October 2008.

5. J. Y. Lee and E. A. Morris, “Breast MRI: historical overview,” in Breast MRI: diagnosis and intervention, E. A. Morris and L. Liberman, Eds., pp. 3–6, Springer, New York, NY, USA, 2005.

6. L. Galluccio, T. Melodia, S. Palazzo, and G. E. Santagati, “Challenges and implications of using ultrasonic communications in intra-body area networks,” in Proceedings of the 9th Annual Conference on Wireless On-Demand Network