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Image Quality in Different Modalities of Medical Imaging with Focus on Mammography

Image Quality in Different Modalities of Medical Imaging with Focus on Mammography. Dr. Nabil Maalej Physics Dept., KFUPM 14-12-2004. Outline. Imaging Modalities (Brief) Image Formation in Mammography Image Quality Contrast Resolution Image Quality Assurance

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Image Quality in Different Modalities of Medical Imaging with Focus on Mammography

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  1. Image Quality in Different Modalities of Medical Imaging with Focus on Mammography Dr. Nabil Maalej Physics Dept., KFUPM 14-12-2004

  2. Outline • Imaging Modalities (Brief) • Image Formation in Mammography • Image Quality • Contrast • Resolution • Image Quality Assurance • Image Enhancement and Computer Aided Diagnosis (Examples)

  3. X-ray Production X-rays are produced in a vacuum tube that accelerates electrons across a high voltage in the order of 100,000 volts. The accelerated electrons strike a target made of tungsten and produce X-rays.

  4. X-ray Pictures Chest X-ray Head X-ray

  5. Digital Angiography It is a diagnostic procedure that produces X-ray pictures of blood vessels. A catheter is inserted in the vessel to inject contrast fluid into the lumen of the blood vessel, which then becomes visible on X-ray images.

  6. Digital Angiography Images Digital Subtraction Angiography (Mistretta, 1980s)

  7. Computerized Tomography (CT) The technique of CT scanning was developed in 1973 by Hounsfield. A thin fan beam of X-rays generated by a conventional X-ray tube passes through a single 'slice' of a patient through to a bank of X-ray detectors.

  8. CT 2-D Images CT Scan of the Abdomen 3-D CT Image of the Head

  9. Diagnostic Ultrasound Ultrasound is a technique for visualizing internal structures in the body using sound waves.

  10. Ultrasound Images Image of the Heart Image of a Fetal Heart

  11. Magnetic Resonance Imaging The technique involves placing the patient in a strong magnetic field. The magnetic field aligns the nuclear spin of atoms in the patient. When the spins relax to the original orientation, they emit radio-waves which are picked up by receiver coils.

  12. Magnetic Resonance Imaging 2-D MRI scan of the brain Functional MRI of The Brain

  13. Image Formation In Mammography

  14. Mammography Machine

  15. Breast Cancer (Highest)

  16. Breast Cancer (Highest) • For the total Saudi population, the most common ten cancers are (1994-1996 Cancer Registry): • Female breast cancer (8.8%), • Liver cancer (7.5%), • Leukemia (7.5%), • Non-Hodgkin's lymphoma (7.3%) • Colo-rectum cancer (5.5%). • Thyroid cancer (5.2%), • Lung cancer (4.7%) • Nervous system cancer (3.9%) • Stomach cancer (3.8%) and • Urinary bladder cancer (3.5%)

  17. Problem in Detection • False negatives: 10-30% of the visible cancers go undetected • False positives: 70-85% of biopsies unnecessary.

  18. What Can We do to Get Best Image? X-ray Source X-ray Beam Compression Paddle Compressed Breast Table Chest Wall Grid Image Detector

  19. IMAGE QUALITY

  20. Imaging Quality Parameters CONTRAST RESOLUTION NOISE

  21. Contrast • Image Contrast is a measure of difference between regions in an image • Image contrast in mammography is due to the difference in linear attenuation coefficient and thickness of different types of tissue

  22. Attenuation Coefficient Contrast decreases toward higher energies  the recommended optimum for mammography is in the region 18 - 33 keV depending on tissue thickness and composition.

  23. Mammography Spectrum

  24. Scattered Radiation and Contrast

  25. I I Ib Ib It It S Contrast Degradation with Scatter

  26. Anti-scatter grid breast leadsepta detector

  27. Resolution • Spatial resolution of an imaging system can be defined in terms of the smallest spacing between two objects that can be imaged clearly • Example for Radiography spatial resolution is about 0.01 mm, for CT it is about 1 mm • Good resolution is essential to see micro-calcifications in a mammogram

  28. Resolution

  29. Measurement of Resolution

  30. Modulation Transfer Function

  31. IMAGE QUALITY ASSURANCE

  32. Contrast Detail Analysis • Contrast detail analysis: an observer reports the size of the smallest object he or she can perceive at a certain contrast level and with a given noise level in the image.

  33. Measuring Contrast Detail Curve

  34. Measuring Contrast Detail Curve

  35. RMI 156 Phantom

  36. RMI 156 Phantom ACR minimum score is 4 visible fibers, 3 speck groups and 3 masses

  37. Importance of Image Quality

  38. Image Enhancement

  39. Digital Mammography Systems • The Fischer Imaging System: 54 m/pixel, a matrix size of 3,072 x 4,800 pixels, 12 bits/pixel • The GE Medical Systems: 100 m/pixel and a matrix size of 1,800 x 2,304 pixels, 14 bits/pixel • The Trex Medical 41  m/pixel and a matrix size of 4,800 x 6,400 pixels, 14 bits/pixel

  40. Anomalies Suggesting Breast Cancer

  41. Image Enhancement • Single Point Processing • Pixel Group Processing • Frequency Domain Processing • Deconvolution • Geometric Transformation • Other Transformations (FT, Wavelet, …

  42. Manual Intensity Windowing (MIW) • A small portion of the full intensity range of an image is selected and then remapped to the full intensity range of the display device • allow exaggeration of small differences in intensity values between the two objects • It is operator dependent

  43. Manual Intensity Windowing (MIW) MIW

  44. Histogram-Based Intensity Windowing (HIW) • Intensity windowing allows a selected subrange of the image intensity values to receive the full contrast of the display device • statistically analyzing the histogram of each image, locating the modes that represent the different breast tissue types (fatty, dense, muscle) or other parts (background). • intensity window range is automatically selected on the basis of the percentile position within the composite breast tissue class

  45. Histogram-Based Intensity Windowing (HIW)

  46. Histogram-Based Intensity Windowing (HIW) HIW

  47. Mixture-Model Intensity Windowing (MMIW) • MMIW provides region-specific intensity window settings for mammograms • It automatically identifies the five major regions in a mammogram: background, uncompressed fat, compressed fat, dense tissue, and muscle • A specific region histogram can be selectively analyzed to determine region-specific intensity window settings • The mean and standard deviation of the intensities in the region are used to parameterize a sigmoidal intensity window function

  48. Mixture-Model Intensity Windowing (MMIW),

  49. Mixture-Model Intensity Windowing (MMIW) MMIW (Dense Tissue)

  50. Unsharp masking • low-pass filtered version of the original image is created and the image values that result are subsequently multiplied by a weighting factor and subtracted from the original image

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