Hadamard Transform Imaging Paul Holcomb Tasha Nalywajko Melissa Walden.

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Hadamard Transform Imaging
Presentation transcript:

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? 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

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

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

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

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

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

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

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

System Diagram Apply Hadamard matrix using DMD Compress image to 160um line

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

System Output

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