Hadamard Transform Imaging

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Hadamard Transform Imaging Paul Holcomb Tasha Nalywajko Melissa Walden

description

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?. - PowerPoint PPT Presentation

Transcript of Hadamard Transform Imaging

Page 1: Hadamard Transform Imaging

Hadamard Transform Imaging

Paul Holcomb

Tasha Nalywajko

Melissa Walden

Page 2: Hadamard Transform Imaging

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

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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

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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

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Design Objective

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

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System Design

Hadamard Transform

• Decreased imaging time

• Increased SNR Hadamard Matrix Definition

Inverse Hadamard Transform

Digital Micro-mirror Device

• Allows use of Hadamard Transform

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Fourier vs. Hadamard Imaging

Wuttig and Riesenburg, “Sensitive Hadamard Transform Imaging Spectrometer”

SNR Increase with Hadamard: √n

SNR Increase with S-Matrix: (√n)/2

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System Diagram

Decrease image size to fit within 512 x 512 matrix

Magnification:~0.4

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System Diagram

Apply Hadamard matrix using

DMD

1

1-1

-1

1

1

-1

-1

Compress image to 160um line

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Disperse light spectrally using

spectrograph and collect image

using CCD camera

Apply inverse Hadamard

transform using computer

X

YSpectrum

System Diagram

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System Output

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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