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Effects of Slice Thickness Filter in Breast Tomosynthesis

Filtered Back Projection Reconstruction

Linlin Cong 1, Weihua Zhou 2, *Ying Chen 1,2

 1Biomedical Engineering Graduate Program

2Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL 62901

(* Corresponding Author)

IEEE GENSIPS 2011

Medical Imaging Laboratory

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OUTLINE

Introductions

Breast Tomosynthesis Imaging

System

Tomosynthesis Image

Reconstruction and Simulation

Results

Conclusions

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Introduction

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Breast Cancer Breast Cancer:

• Most common cancer among women worldwide;

• Second leading cause of cancer related death among women.

Symptoms:• No symptom in the early stage, regular

breast exams are important;• Breast lump or lump in the armpit,

change in the size, shape, fluid from the nipple.

• Once the patient is diagnosed with breast cancer, next step is staging (Grade: 0, I, II, III, IV). Higher the grade is, poorer the outcome of the treatment will be.

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Mammography

Traditional mammography:• Currently, a standard and important clinical

screening and diagnosis for early detection of breast cancer;

• Cheap, low radiation dosage. Limitations of traditional mammography:

• 20% false negative rate, many call backs from screening;

• low positive predictive value, about 30% of breast cancers are still missed in mammography;

• 2D imaging system, difficult to distinguish a cancer from overlapped breast tissues.

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Breast Tomosynthesis

3D slice images provide depth information

Improve conspicuity of structure by removing the visual clutter associated with overlying anatomy

Promising to reduce recall rates, and to increase cancer detection accuracy.

Low dosage; relatively cheap Extensive attentions from academic

communities and industrial vendors have been paid to this promising field.

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Breast Tomosynthesis Imaging System

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Siemens Mammomat Inspiration

GEIMS GIOTTO Hologic Selenia Dimensions

Examples of current commercial breast tomosynthesis prototype systems :

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Most of these systems re-utilize the traditional partial isocentric mammography design.

X-ray tube moves in an arc across the breast

Series of low dosage images are acquired at different angles

Limitation is X-ray tube’s movement may introduce motion blur and cause patients’ discomfort.

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A Novel Nanotechnology Enabled Digital Breast Tomosynthesis

Prototype System Invented by our collaborators at the

University of North Carolina Chapel Hill Built up with fixed multi-beam field-

emission X-ray sources, no movement of X-ray tubes;

Total scanning time: about 11.2 seconds for typical 25 projection views

Advantages:• No motion blur• Less scanning time, so decreasing the

waiting time

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A novel multi-beam x-ray source developed by Zhou Lu et al.

• Fixed multi-beam field-emission x-ray (MBFEX) sources based on unique properties of carbon nanotube electron emitters.

• The total scan time for a typical 25 views is about 11.2 seconds.

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Tomosynthesis Image Reconstruction and

Simulation

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BREAST TOMOSYNTHESIS IMAGING SYSTEM SIMULATION

The image acquisition system we used to get the projection images was simulated based on the parallel imaging system.

• 25 X-ray sources.

• The path of tubes is parallel to the plane of detector.

• Two sets of data were simulated to investigate the filter effects:

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The image acquisition system:

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IMAGING SYSTEM: Data 1 One Sphere:

• placed at 30mm above the detector • radius = 5mm.

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IMAGING SYSTEM: Data 2 Two overlapping spheres were simulated.

• Sphere 1: height = 20mm above detector, radius = 5mm• Sphere 2: height = 40mm above detector, radius = 10mm

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Reconstruction Algorithm

• Mathematic Reconstruction Methods: Shift and Add (SAA) Backprojection(BP)

• Filter-based Reconstruction Methods: Filtered Backprojection(FBP) Matrix Inversion Tomosynthesis (MITS)

• Statistical Reconstruction Methods: Maximum Likelihood Expectation

Maximization(MLEM)

• Algebraic Reconstruction Methods: Simultaneous Algebraic Reconstruction

Technique (SART)

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Reconstruction Algorithm

• Mathematic Reconstruction Methods: Shift and Add (SAA) Backprojection(BP)

• Filter-based Reconstruction Methods: Filtered Backprojection(FBP) Matrix Inversion Tomosynthesis (MITS)

• Statistical Reconstruction Methods: Maximum Likelihood Expectation

Maximization(MLEM)

• Algebraic Reconstruction Methods: Simultaneous Algebraic Reconstruction

Technique (SART)

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Filtered Back Projection (FBP) Ramp Filter:

• To suppress the component in low x frequency(x)

• strengthen high frequency (x) part.

Low-pass Filter(Hamming Window):• To suppress noise

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FBP: Profile Filter

To reduce the effects caused by discontinuation of the z-border with a sharp step function

Appled along the Z direction Equation:

Hprofile_filter

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Results

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Impulse Responses Analysis

a) Impulse response without profile filter

b) Impulse response with profile filter

c) Intensity profiles of figure (a) d) Intensity profiles of figure (b)

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Single Sphere Data

a) Reconstructed image of 30mm plane without profile filter

c) Reconstructed image of 30mm plane with profile filter

b) Vertical plane of the object along Z-direction without profile filter

d) Vertical plane of the object along Z-direction with profile filter

e) Intensity profiles of figure (a) f) Intensity profiles of figure (b)

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Two Overlapping Sphere Data

a) Reconstructed image of 20mm plane without profile filter

b) Reconstructed image of 40mm plane without profile filter

c) Reconstructed image of 20mm plane with profile filter

d) Reconstructed image of 40mm plane with profile filter

e) Vertical plane of objects along Z-direction without profile filter

f) Vertical plane of objects along Z-direction with profile filter

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CONCLUSIONS

Effects of Profile Filter:• Enhance the sharpness

• Reduce the ringing artifacts

• Make the reconstructed objects spread out more uniformly along the depth (z) direction

• Reduce the mutual interference between objects located on the neighboring slices

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ACKNOWLEDGMENT

• We thank our collaborators at The University of North Carolina at Chapel Hill (UNC) and group members at Southern Illinois University (SIU).

• The related work has been supported by Southern Illinois University and U.S. National Institutes of Health (NIH/NCI R01 CA134598-01A1).

Medical Imaging Laboratory