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Hadamard Transform Imaging

Hadamard Transform Imaging. Paul Holcomb Tasha Nalywajko Melissa Walden. Problem Definition. Current 3D imaging systems for brain surgery are too slow and possess too low of a resolution to be effective in an operating room setting. Why is this important?.

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Hadamard Transform Imaging

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  1. Hadamard Transform Imaging Paul Holcomb Tasha Nalywajko Melissa Walden

  2. Problem Definition • Current 3D imaging systems for brain surgery are too slow and possess too low of a resolution to be effective in an operating room setting

  3. Why is this important? • 71% mortality rate for diagnosed brain tumors • Correlation between complete resectioning of tumors and improved prognosis • Complete resectioning requires knowing the location of the tumor, especially tumor margins • Imaging in a clinical setting should be fast • Operating room billed by the quarter- or half hour

  4. Cost/Benefit Analysis • Treatment costs: • OR cost: $10K - $15K per surgery (depending on length) • ICU: $1963/24 hrs • Floor: $779/24 hrs • Chemotherapy • Radiation therapy Cost Reduction: • Shorter surgeries • Less time in hospital (ICU or floor) • Less post-surgical treatment required

  5. Design Criteria • Must produce an image in real time • Must accurately reproduce area of interest in the brain • Must distinguish healthy versus tumor tissue • Must be small enough to be usable in an operating room setting • Must interface with operating microscope

  6. Design Objective Construct imaging system using digital micro-mirror device and Hadamard transform for use with operating microscope in a clinical setting

  7. System Design • Hadamard Transform • Decreased imaging time • Increased SNR Hadamard Matrix Definition Inverse Hadamard Transform • Digital Micro-mirror Device • Allows use of Hadamard Transform

  8. Fourier vs. Hadamard Imaging SNR Increase with Hadamard: √n SNR Increase with S-Matrix: (√n)/2 Wuttig and Riesenburg, “Sensitive Hadamard Transform Imaging Spectrometer”

  9. System Diagram Illuminate sample with white light Collect and collimate reflected light

  10. System Diagram Decrease image size to fit within 512 x 512 matrix Magnification:~0.4

  11. 1 -1 1 -1 -1 1 1 -1 System Diagram Apply Hadamard matrix using DMD Compress image to 160um line

  12. System Diagram Disperse light spectrally using spectrograph and collect image using CCD camera Apply inverse Hadamard transform using computer X Y Spectrum

  13. System Output

  14. Design Timeline February: Align and test Stage 1; align DMD; align and test Stage 2 March: Insert, align, and test spectrograph; test system using reflectance standard to determine SNR; test system using normal and tumor tissue samples April: Continue testing and analysis; compile and present findings at Senior Design Day

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