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Slice profile ieee2011_siu

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Slice profile ieee2011_siu

  1. 1. 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 1
  2. 2. OUTLINE Introductions Breast Tomosynthesis Imaging System Tomosynthesis Image Reconstruction and Simulation Results Conclusions 2
  3. 3. Introduction 3
  4. 4. 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 4
  5. 5. 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. 5
  6. 6. 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. 6
  7. 7. Breast Tomosynthesis Imaging System 7
  8. 8.  Examples of current commercial breast tomosynthesis prototype systems : SiemensMammomat IMS GIOTTO Hologic Selenia Dimensions GEInspiration 8
  9. 9.  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. 9
  10. 10. 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 10
  11. 11. • Fixed multi-beam field- emission x-ray (MBFEX) sources based on unique properties of carbon nanotube electron emitters. • The total scan time for aA novel multi-beam x-ray source typical 25 views is about developed by Zhou Lu et al. 11.2 seconds. 11
  12. 12. Tomosynthesis Image Reconstruction and Simulation 12
  13. 13. 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: 13
  14. 14.  The image acquisition system: 14
  15. 15. IMAGING SYSTEM: Data 1 One Sphere: • placed at 30mm above the detector • radius = 5mm. 15
  16. 16. 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 16
  17. 17. 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) 17
  18. 18. 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) 18
  19. 19. Filtered Back Projection (FBP) 19
  20. 20. FBP: Profile Filter 20
  21. 21. Results 21
  22. 22. Impulse Responses Analysis a) Impulse response without b) Impulse response profile filter with profile filterc) Intensity profiles of figure (a) d) Intensity profiles of figure (b) 22
  23. 23. Single Sphere Dataa) Reconstructed b) Vertical plane of c) Reconstructed d) Vertical plane ofimage of 30mm the object along image of 30mm the object along Z-plane without Z-direction without plane with direction withprofile filter profile filter profile filter profile filtere) Intensity profiles of figure (a) f) Intensity profiles of figure (b) 23
  24. 24. Two Overlapping Sphere Dataa) Reconstructed b) Reconstructed c) Reconstructed d) Reconstructedimage of 20mm image of 40mm image of 20mm image of 40mmplane without plane without plane with plane withprofile filter profile filter profile filter profile filter e) Vertical plane of objects f) Vertical plane of objects along Z-direction without along Z-direction with profile profile filter filter 24
  25. 25. 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 25
  26. 26. 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 26

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