Dr. Karin Toepfer Profile

Dr. Karin Toepfer

Principal Image Scientist

SPIE Involvement:

Author | Instructor

Proceedings Article | 3 March 2011 Paper

The effect of defect cluster size and interpolation on radiographic image quality

Karin Töpfer, Kwok Yip

Proceedings Volume 7966, 79660V (2011) https://doi.org/10.1117/12.878289

KEYWORDS: Image quality, Sensors, Medical imaging, Diagnostics, Image analysis, Lung, Standards development, Image quality standards, Visibility, Radiography

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Proceedings Article | 14 March 2009 Paper

Optimized operation and offset corrections for a battery-powered wireless digital x-ray detector

Karin Töpfer, John Dehority

Proceedings Volume 7258, 72583O (2009) https://doi.org/10.1117/12.811218

KEYWORDS: Sensors, Image quality, Image processing, X-rays, X-ray detectors, Calibration, X-ray imaging, Detection and tracking algorithms, Electronics, Surgery

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Proceedings Article | 20 March 2007 Paper

Advanced system model for the prediction of the clinical task performance of radiographic systems

Karin Töpfer, Brian Keelan, Francisca Sugiro

Proceedings Volume 6515, 651512 (2007) https://doi.org/10.1117/12.709570

KEYWORDS: Sensors, Lung, Systems modeling, Dual energy imaging, Modulation transfer functions, Image processing, Visual process modeling, Radiography, Interference (communication), Target detection

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A flexible software tool was developed that combines predictive models for detector noise and blur with image simulation and an improved human observer model to predict the clinical task performance of existing and future radiographic systems. The model starts with high-fidelity images from a database and mathematical models of common disease features, which may be added to the images at desired contrast levels. These images are processed through the entire imaging chain including capture, the detector, image processing, and hardcopy or softcopy display. The simulated images and the viewing conditions are passed to a human observer model, which calculates the detectability index d' of the signal (disease or target feature). The visual model incorporates a channelized Hotelling observer with a luminance-dependent contrast sensitivity function and two types of internal visual system noise (intrinsic and image background-induced). It was optimized based on three independent human observer studies of target detection, and is able to predict d' over a wide range of viewing conditions, background complexities, and target spatial frequency content. A more intuitive metric of system performance, Task-Specific Detective Efficiency (TSDE), is defined to indicate how much detector improvements would translate to better radiologist performance. The TSDE is calculated as the squared ratio of d' for a system with the actual detector and a hypothetical system containing an ideal detector. A low TSDE, e.g., 5% for the detection of 0.1 mm microcalcifications in typical mammography systems, indicates that improvements in the detector characteristics are likely to translate to better detection performance. The TSDE of lung nodule detection is as high as 75% even with the detective quantum efficiency (DQE) of the detector not exceeding 24%. Applications of the model to system optimizations for flat-panel detectors, in mammography and dual energy digital radiography, are discussed.

Proceedings Article | 12 April 2005 Paper

Effect of grayscale resolution on the performance of lung nodule detection on a softcopy display

W. James Sehnert, Brian Keelan, Karin Toepfer

Proceedings Volume 5744, (2005) https://doi.org/10.1117/12.593766

KEYWORDS: Heart, Lung, LCDs, Calibration, Video, Sensors, Image resolution, Chest, X-rays, Selenium

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Proceedings Article | 17 January 2005 Paper

Update on the INCITS W1.1 standard for evaluating the color rendition of printing systems

Susan Farnand, Karin Topfer, William Kress, Oscar Martinez, Ann McCarthy, Helen Shin, Eric Zeise, Dmitri Gusev

Proceedings Volume 5668, (2005) https://doi.org/10.1117/12.591301

KEYWORDS: Printing, Quantization, Image quality, Image quality standards, Visualization, Digital imaging, Digital image correlation, Skin, Photography, Inkjet technology

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Proceedings Article | 4 May 2004 Paper

Relative impact of detector noise and anatomical structure on lung nodule detection

Brian Keelan, Karin Topfer, John Yorkston, William Sehnert, Jacquelyn Ellinwood

Proceedings Volume 5372, (2004) https://doi.org/10.1117/12.536733

KEYWORDS: Lung, Sensors, Heart, Signal to noise ratio, X-rays, X-ray imaging, Modulation transfer functions, Chest, X-ray detectors, Signal detection

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Proceedings Article | 18 December 2003 Paper

Update on INCITS W1.1 standard for evaluating the color rendition of printing systems

Robert Cookingham, Edul Dalal, Susan Farnand, Dmitri Gusev, William Kress, Oscar Martinez, Ann McCarthy, Karin Topfer, Eric Zeise

Proceedings Volume 5294, (2003) https://doi.org/10.1117/12.531035

KEYWORDS: Quantization, Printing, Image quality, Image quality standards, Visualization, Digital image correlation, Digital imaging, Skin, Photography, Inkjet technology

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Showing 5 of 7 publications

Course Instructor

SC593: Characterization and Prediction of Image Quality

This course explains how to evaluate the quality of an image using numerical scales and physical standards; and how to predict the distribution of quality that would be produced by a pictorial imaging system under conditions of actual customer use. A framework is presented for conducting calibrated, extensible psychometric research so that results from different experiments can be rigorously integrated to construct predictive software using Monte Carlo simulations. Development of generalized objective metrics correlating with perceptual attributes based on psychometric data is discussed in detail and a number of examples of practical applications to product design are provided.

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