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BMED-4800/ECSE-4800 Introduction to Subsurface Imaging Systems Lecture 5: X-ray Imaging (cont.) Kai E. Thomenius1 & Badri Roysam2 1Chief Technologist, Imaging Technologies, General Electric Global Research Center 2Professor, Rensselaer Polytechnic Institute Center for Sub-Surface Imaging & Sensing Review of Last Lecture Quick historical review of X-rays was given. Block diagrams, key components defined. Brief discussion of x-ray scattering An X-ray beam, traversing through an object, is attenuated by the exponential Lambert-Beer Law. The product of the attenuation coefficient and the path length of the x-ray beam in such a target is critical in establishing detectability. Today: Digital Detectors, X-ray Metrics Outline of Course Topics THE BIG PICTURE What is subsurface imaging? Why a course on this topic? EXAMPLE: Projection Imaging X-Ray Imaging Computer Tomography COMMON FUNDAMENTALS Propagation of waves Interaction of waves with targets of interest PULSE ECHO METHODS Examples MRI A different sensing modality from the others Basics of MRI MOLECULAR IMAGING What is it? PET & Radionuclide Imaging IMAGE PROCESSING & CAD /meetings/amos2/pdf/26-5959-83142-414.pdf Digital Detector Front End /meetings/amos2/pdf/26-5959-83142-414.pdf Detector Details /meetings/amos2/pdf/26-5959-83142-414.pdf Selenium based Detector /meetings/amos2/pdf/26-5959-83142-414.pdf Performance Metrics Signal-to-noise Ratio (SNR) SNR determines the detectability of an object Signal derived from x-ray quanta Noise comes from a variety of sources: X-ray quantum statistics, Poisson distribution Electronic noise Sampling noise Anatomical noise Signal processing steps critical to image quality Correction for detector variability, defects Post-process filtering FP vessel 12 mm large cell lung cancer Quantum noise For a digital x-ray detector system with square pixels if the average number of x-rays recorded in each pixel is N, then the noise (per pixel) will be Statistical distribution associated with x-rays is the Poisson distribution. The above relation falls out directly from this fact. Poisson Distribution Poisson Distribution is a probability distribution given by If the expected no. of occurrences in a space is l, then the probability that there are exactly k occurrences is given by f(k,l) Signal-to-noise ratio The signal-to-noise ratio (SNR) is given by When the number of x-rays, N, is increased, the radiation dose also increases. To double the SNR, the dose to the patient needs to be increased by a factor of 4 Contrast-to-noise ratio (CNR) for any two intensities (I1 and I2) at a detector is given by Here N is the nominal value of photons reaching the detector. Other Measures of Image Quality Limiting Spatial Resolution (LSR) The highest frequency that can be visualized Modulation Transfer Function (MTF) Measures how the detector passes signal, as a function of spatial frequency MTF = Modulation at detector output Modulation at detector input Spatial Frequency (cycles/mm) MTF 1.0 0 0.03 - 0.05 LSR MTF=1 in out q(x) 2A(f) q(x) 2A(f) Source: 9/info/download/etc/breastx/93/93-04.ppt MTF=0.5 Modulation Transfer Function (MTF) / Spatial resolution: An imaging systems ability to render the contrast of an object as a function of object detail. in out q(x) 2A(f) I(x) 2Aout(f) MTF Modulation Transfer Function LSR Screen-film has LSR 20 lp/mm corresponds to 25 mm pixel Digital (GE) 100 mm pixel Sources of MTF degradation Lateral spread of light in scintillator limited by CsI needles increases with scintillator thickness Lateral spread of secondary x- rays not significant away from k- edges of Cs and I Sampling aperture of pixel: sinc(fx*a)sinc(fy*a) Spatial Frequency (cycles/mm) M T F Digital Imager Film-Screen If films LSR is better than digital why do we see improved performance in digital? MTF For Direct, Indirect, and Screen Film Measures of Image Quality-DQE Detective Quantum Efficiency, DQE SNR gives the transfer function of both signal and noise DQE = SNR2 at detector output SNR2 at detector input SNR2 at detector output Patient Dose DQE Spatial Frequency (cycles/mm) DQE Digital Imager Film-Screen 1.0 High DQE in low-to-mid frequencies aids detection. High DQE in high frequencies aids characterization. The higher the DQE, the higher the SNR, and the greater the probability of detection. where f is the spatial frequency (lp/mm), X is the exposure (mR) and : S = Median Signal Level (cts), i.e. amplitude of information MTF = Modulation Transfer Function NPS = Noise Power Spectrum (cts2 * mm2) C = Incident Xray Fluence (xrays / (mm2 * mR) DQE describes the measured SNR in relation to an ideal detector. SNR2 is deduced from the ratio of MTF2 (signal2) to the NPS (noise2) DQE : Definition /meetings/amos2/pdf/26-5959-83142-414.pdf Calibration of Digital Detector Dark Image Offset Diode leakage FET charge retention Electronic noise Calibration of Digital Detector Offset Corrected Dark Image Electronic Noise Calibration of Digital Detector Offset Calibrated Amplifier gain variation Pixel-to-pixel gain variation Calibration of Digital Detector Offset and Gain calibrated Flood exposed image Poisson statistical x-ray noise Electronic noise Apply Corrections Low dose: before and After Offset Correction Apply Corrections High dose Tomosynthesis Advanced Applications Tomosynthesis- 3D X-ray 3D Breast Imaging - Tomosynthesis 3D imaging addresses the major problem with mammography today superimposed tissue 3D imaging may enable compression reduction Tissue immobilization vs. compression Compliance with screening protocols Single tomo exam in MLO position may replace conventional mammography, potentially enabling dose reduction Tomosynthesis Concept Prototype System Parameters Prototype based on GEMS Senographe DMR, Revolution flat panel detector, motorized tube motion assembly 11 projections over +/- 25 degrees 7.5 sec patient exam time Total dose 1.5x a single mammographic view 0.75x a standard mammographic screening exam 100 micron pixels 1 mm (3d) slice separation Tomosynthesis Goal: Limited 3-D reconstruction to remove overlying/underlying structure All image planes visualized using a single acquisition Acquisition: Vertical tube motion Total tube angle: 5 -15 Number of Projected Images: 15 25 Exam length: 5 -10 sec (single breath- hold) Slice thickness: 1 cm Enabled by GE Revolution detector: Courtesy of Duke University and Wake Forest Medical Center Rotational Axis Tube vertical motion Small Changes to Rad System allows for 3D Imaging! Image Reconstruction in Tomo Data incompleteness From a CT perspective, data is very sparse Limited angular range (z-resolution) Insufficient angular sampling (streaks) Truncated projections (inconsistency) Reconstruction Concept Shift and Add Add Reconstruction of single plane Projections at different angles Shift Vertical slice through object Reconstruction of vertical slice through object Artifacts: Out-of-plane structures appear as N low-contrast copies (N = # of projections). Contrast / “blurring” of artifacts depends on N, projection angles / tube trajectory, etc. An Example Standard 2D x- ray Images courtesy of Dr. Dan Kopans- MGH Tomosynthesis Missed Cancer Spiculated Lesion Standard Mammogram MLO Tomo Slice MLO Tomosynthesis Images courtesy of Dr. Dan Kopans- MGH An Example 3D Tomosynthesi s Images courtesy of Dr. Dan Kopans- MGH Rad Tomo Example Low Dose 3D Imaging! Receiver Operating Characteristics Receiver Operating Characteristic (ROC) curves Most basic task of the diagnostician is to separate abnormal subjects from normal subjects In many cases there is significant overlap in terms of the appearance of the image Some abnormal patients have normal-looking films Some normal patients have abnormal-looking films ROC curves are a tool for assessing the performance of a hypothesis testing algorithms. 2 x 2 Decision Matrix Actually Abnormal Actually Normal Diagnosed as Abnormal True Positive (TP) False Positive (FP) Diagnosed as Normal False Negative (FN) True Negative (TN) ROC curves (cont.) For a single threshold value and the population being studied, a single value for TP, TN, FP, and FN can be computed The sum TP + TN + FP + FN will be equal to the total number of normals and abnormals in the study population “True” diagnosis must be determined independently, based on biopsy confirmation, long- term patient follow-up, etc. Summary Design of digital x-ray detectors was described. Performance metrics (MTF, DQE) for x- ray performance were given. Justification for digital detectors was based on these. Tomosynthesis concept introduced. Brief review of ROC methods for hypothesis testing was given. Next time: Introduction to CT Scanners Homework Using web resources (or sources given below), describe the key steps of the direct conversion process with amorphous Selenium. How are x- rays converted to electrons? What is