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Medical Image Analysis Introduction Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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Modalities X-ray Computed Tomography (X-ray CT) Magnetic Resonance Imaging (MRI) Single Photon Emission Computed Tomography (SPECT) Positron Emission Tomography (PET) Ultrasound
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An X-ray mammogram Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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An X-ray CT
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A PET Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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An MRI Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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Figure 1.1. A collaborative multidisciplinary paradigm of medical imaging research and applications.
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Medical image modalities ◦ Energy ◦ Anatomical, physiological, or functional ◦ External, internal, or combination Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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10 -10 Radio Waves TV Waves Radar Waves Microwaves Infrared Rays Visible Light Ultraviolet Rays X-rays Gamma Rays 10 2 10 1 1 10 -1 10 -2 10 -3 10 -4 10 -6 10 -7 10 -8 Wavelength in meters Frequency in Hz 10 -5 10 -9 10 -10 10 -11 10 -12 10 -13 10 -14 10 3 10 6 10 7 10 910 10 11 10 12 10 14 10 15 10 16 10 13 10 17 10 18 10 19 10 20 10 21 10 22 10 5 10 8 Energy in eV 10 -9 10 -8 10 -6 10 -5 10 -4 10 -3 10 -1 110 1 10 -2 10 2 10 3 10 4 10 5 10 6 10 7 10 -7 MRI X-ray Imaging Gamma-ray Imaging Cosmic Rays Figure 1.2: Different sources of imaging modality in the electromagnetic spectrum.
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Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003. Sourceof Energy Used for Imaging External Internal Combination: External and Internal Nuclear Medicine: Single Photon EmissionTomography (SPECT) Nuclear Medicine: Positron Emission Tomography (PET) Magnetic Resonance Imaging: MRI, PMRI, FMRI Optical Fluorescence Imaging Electrical Impedance Imaging Medical Imaging Modalities X-Ray Radiographs X-Ray Mammography X-Ray Computed Tomography Optical Transmission andTransillumination Imaging Ultrasound Imaging and Tomography
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From Physiology to Information Processing Understanding image medium ◦ Tissue density, blood flow, perfusion, cardiac motion Physics of imaging ◦ Transmission of X-rays, emission of gamma rays, MR imaging Imaging instrumentation ◦ Collecting the data, signal-to-noise ratio, resolution Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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Data acquisition methods for image formation ◦ Active filtering, post-processing methods ◦ Back-projection, iterative and Fourier transform methods Imaging processing and analysis ◦ Enhancement, transformations, features of interest Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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General Performance Measures Positive: Object was observed Negative: Object was not observed True Positive False Negative True Negative False Positive Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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True Positive True Negative False Negative False Positive True Condition Object is present. Object is NOT present. Object is observed. Object is NOT observed. Observed Information Figure 1.4. A conditional matrix for defining four basic performance measures as defined in the text.
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Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003. TNF TPF b a c Figure 1.5: ROC curves with curve “a” indicating better overall classification ability than the curve “b” while the curve “c” shows the random probability.
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Sensitivity Specificity Accuracy Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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An example of feature-adaptive contrast enhancement processing as applied to a mammogram to enhance microcalcification areas ◦ Histogram equalization Figures come from the textbook: Medical Image Analysis, by Atam P. Dhawan, IEEE Press, 2003.
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Figure 1.6. (a) A part of the digitized breast film-mammogram with microcalcification areas. (b): Enhanced image through feature adaptive contrast enhancement algorithm. (c): Enhanced image through histogram equalization method.
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