R. E. Johnston

Diffraction enhanced x-ray imaging

Diffraction enhanced imaging is a new x-ray radiographic imaging modality using monochromatic x-rays from a synchrotron which produces images of thick absorbing objects that are almost completely free of scatter. They show dramatically improved contrast over standard imaging applied to the same phantom. The contrast is based not only on attenuation but also the refraction and diffraction properties of the sample. This imaging method may improve image quality for medical applications, industrial radiography for non-destructive testing and x-ray computed tomography.

Contrast-limited adaptive histogram equalization: speed and effectiveness

An experiment intended to evaluate the clinical application of contrast-limited adaptive histogram equalization (CLAHE) to chest computer tomography (CT) images is reported. A machine especially designed to compute CLAHE in a few seconds is discussed. It is shown that CLAHE can be computed in 4 s after 5-s loading time using the specially designed parallel engine made from a few thousand dollars worth of off-the-shelf components. The processing appears to be useful for a wide range of medical images, but the limitations of observer calibration make it impossible to demonstrate such usefulness by agreement experiments.<<ETX>>

Diffraction enhanced imaging contrast mechanisms in breast cancer specimens

We have investigated the contrast mechanisms of the refraction angle, and the apparent absorption images obtained from the diffraction enhanced imaging technique (DEI) and have correlated them with the absorption contrast of conventional radiography. The contrast of both the DEI refraction angle image and the radiograph have the same dependence on density differences of the tissues in the visualization of cancer; in radiography these differences directly relate to the contrast while in the DEI refraction angle image it is the density difference and thickness gradient that gives the refraction angle. We show that the density difference of fibrils in breast cancer as measured by absorption images correlate well with the density difference derived from refraction angle images of DEI. In addition we find that the DEI apparent absorption image and the image obtained with the DEI system at the top of the reflectivity curve have much greater contrast than that of the normal radiograph (x8 to 33-fold higher). This is due to the rejection of small angle scattering (extinction) from the fibrils enhancing the contrast.

Medical applications of diffraction enhanced imaging.

We have developed a new X-ray imaging technique, diffraction enhanced imaging (DEI), which can be used to independently visualize the refraction and absorption of an object. The images are almost completely scatter-free, allowing enhanced contrast of objects that develop small angle scattering. The combination of these properties has resulted in images of mammography phantoms and tissues that have dramatically improved contrast over standard imaging techniques. This technique potentially is applicable to mammography and other fields of medical X-ray imaging and to radiology in general, as well as possible use in nondestructive testing and X-ray computed tomography. Images of various tissues and materials are presented to demonstrate the wide applicability of this technique to medical and biological imaging.

Perceptual linearization of video-display monitors for medical image presentation

The perceptual linearization of video display monitors plays a significant role in medical image presentation. First, it allows the maximum transfer of information to the human observer. Second, for an image to be perceived as similarly as possible when seen on different displays, the two displays must be standardized. Third, perceptual linearization allows us to calculate the perceived dynamic range of the display device, which allows comparison of the maximum inherent contrast resolution of different devices. This paper provides insight into the process of perceptual linearization by decomposing it into the digital driving level to monitor luminance relationship, the monitor luminance to human brightness perception relationship, and the construction of a linearization function derived from these two relationships. We compare and contrast the results of previous work with recent experiments in our laboratory and related work in vision and computer science. Based on these analyses we give recommendations for using existing methods when appropriate, and propose new methods or suggest additional work where the current methods fall sort. Finally, we summarize the significant issues from all three component areas.

How many screens does a CT workstation need

A considerable number of prototype and commerical workstations have been developed during the last 10 years for electronic display of computed tomographic (CT) images during clinical interpretation. These CT workstations have varied widely in the number and size of monitors available for the display of the medical images ranging from a single 1,024×1,204-pixel monitor, to eight 2,500×2,000-pixel monitors. Image display times also have varied considerably, ranging from as fast as. 11 seconds, to as slow as 26 seconds to fill a single monitor. No consensus has formed in the workstation community with regard to display area and response time requirements. To address this issue, we have constructed a time-motion model of CT interpretation. Model accuracy is experimentally verified with three workstations as well as with the film alternator. In general, CT interpretations with an electronic workstation become faster as display area increases and display time decreases. Results can be used by workstation designers and purchasers to roughly estimate differences in interpretation speeds among contending CT workstation designs.

Evaluation and optimization of contrast enhancement methods for medical images

We have developed and are applying two methods of image quality assessment with the aim of optimizing contrast enhancement parameter settings and evaluating competing methods. Our first approach uses observer studies employing psychophysical methods and a realistic clinical task; the second incorporates a model of human vision in a computer simulation of the performance of an observer.

Visual psychophysics and medical imaging: nonparametric adaptive method for rapid threshold estimation in sensitivity experiments

The M-AFC (alternatively forced choice) transformed up-down adaptive method for the rapid determination of visual thresholds in medical images is described. The method is very efficient in obtaining thresholds to medical imaging parameters; in addition, it is free from criterion bias, an important concern in radiology, and it is free from parametric assumptions about the stimulus scale, which is often unknown due to the complexity of medical images. Issues of experimental design are presented that arise in the use of this method, and the psychological caveats which should be followed with human observers are noted. Two experiments are presented to demonstrate the methods efficacy in determining thresholds and psychometric functions in medical images.

Evaluation of digital processing methods for the display of digital mammography

One of the advantages of digital mammography is the ability to acquire a mammography image with a larger contrast range. With this advantage comes the tradeoff of how to display this larger contrast range. Laser printed film, and video display both have smaller dynamic ranges than standard mammography film-screen systems. This work examines performance and preference studies for display processing methods for digital mammograms.

DIFFRACTION ENHANCED IMAGING OF SOFT TISSUES

Z. ZHONG , D. CHAPMAN, D. CONNOR , A. DILMANIAN, N. GMUR , M. HASNAH, R. E. JOHNSTON, M. Z. KISS, J. LI , C. MUEHLEMAN-, O. OLTULU, C. PARHAM, E. PISANO, L. RIGON , D. SAYERS, W. THOMLINSON, M. YAFFE, AND H. ZHONG 1 2 NSLS, Brookbaven National Lab., Upton, NY 11973, USA Biological, Chemical and Physical Sci., Illinois lnst. Tech., Chicago, IL 60616, USA Dept. Physics, North Carolina State Univ., Raleigh, NC 27695, USA Medical Dept., Brookhaven National Lab., Upton, NY 11973, USA Dept. Biochemistry, Anatomy, Rush Med. College, Chicago, IL 60612, USA Biomed. Eng., Radiology, Univ. North Carolina, Chapel Hill, NC 27599, USA Dept. Physics, Univ. of Trieste and INFN, Sezione di Trieste, Italy ESRF, F-38043, Grenoble Cedex, France 11 Med. Imaging and Med. Biophysics, Univ. Toronto, Ontario, M4N3M5, Canada Dept. Mechanical Engineering, Univ. Akron, Akron, OH 44325-3903, USA