R. Eugene Johnston

Contrast Limited Adaptive Histogram Equalization image processing to improve the detection of simulated spiculations in dense mammograms

The purpose of this project was to determine whether Contrast Limited Adaptive Histogram Equalization (CLAHE) improves detection of simulated spiculations in dense mammograms. Lines simulating the appearance of spiculations, a common marker of malignancy when visualized with masses, were embedded in dense mammograms digitized at 50 micron pixels, 12 bits deep. Film images with no CLAHE applied were compared to film images with nine different combinations of clip levels and region sizes applied. A simulated spiculation was embedded in a background of dense breast tissue, with the orientation of the spiculation varied. The key variables involved in each trial included the orientation of the spiculation, contrast level of the spiculation and the CLAHE settings applied to the image. Combining the 10 CLAHE conditions, 4 contrast levels and 4 orientations gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 40 backgrounds. Twenty student observers were asked to detect the orientation of the spiculation in the image. There was a statistically significant improvement in detection performance for spiculations with CLAHE over unenhanced images when the region size was set at 32 with a clip level of 2, and when the region size was set at 32 with a clip level of 4. The selected CLAHE settings should be tested in the clinic with digital mammograms to determine whether detection of spiculations associated with masses detected at mammography can be improved.

A method for determination of optimal image enhancement for the detection of mammographic abnormalities

We present a paradigm for empirical evaluation of digital image enhancement algorithms for mammography that uses psychophysical methods for implementation and analysis of a clinically relevant detection task. In the experiment, the observer is asked to detect and assign to a quadrant, or indicate the absence of, a simulated mammographic structure characteristic of cancer embedded in a background image of normal breast tissue. Responses are indicated interactively on a computer workstation. The parameter values for the enhancement applied to the composite image may be varied on each trial, and structure detection performance is estimated for each enhancement condition. Preliminary investigations have provided insight into an appropriate viewing duration, and furthermore, suggest that nonradiologists may be used under this methodology for the tasks investigated thus far, for predicting parameter values for clinical investigation. We are presently using this method in evaluating several contrast enhancement algorithms of possible benefit in mammography. These methods enable an objective, clinically relevant evaluation, for the purpose of optimal parameter determination or performance assessment, of digital image-processing methods potentially used in mammography.

Introduction to perceptual linearization of video display systems for medical image presentation.

The perceptual linearization of video display systems should play a significant role in medical image presentation. It maximizes the faithfulness of information transfer to the human observe; it provides a method for standardizing the appearance of images across different display devices; and it allows for calculation of the inherent contrast resolution of different display 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. A discussion of previous work in these areas is given. We then compare and contrast the results of previous work with recent experiments in our laboratory and related work in vision and computer science. We conclude that (1) sufficiently good visual models exist for agreeing on a standard method of calculating the perceptual linearization function; (2) improvements in the resolution and luminance distribution of the digitalto-analog circuitry in display systems are required for medical imaging; and (3), methods for calculating a linearization remapping from a perceptual linearization function currently have significant error and should be replaced with methods that minimize perceptual error.

The effect of intensity windowing on the detection of simulated masses embedded in dense portions of digitized mammograms in a laboratory setting

The purpose of this study was to determine whether intensity windowing (IW) improves detection of simulated masses in dense mammograms. Simulated masses were embedded in dense mammograms digitized at 50 microns/pixel, 12 bits deep. Images were printed with no windowing applied and with nine window width and level combinations applied. A simulated mass was embedded in a realistic background of dense breast tissue, with the position of the mass (against the background) varied. The key variables involved in each trial included the position of the mass, the contrast levels and the IW setting applied to the image. Combining the 10 image processing conditions, 4 contrast levels, and 4 quadrant positions gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 160 backgrounds. The entire experiment consisted of 800 trials. Twenty observers were asked to detect the quadrant of the image into which the mass was located. There was a statistically significant improvement in detection performance for masses when the window width was set at 1024 with a level of 3328. IW should be tested in the clinic to determine whether mass detection performance in real mammograms is improved.

Does intensity windowing improve the detection of simulated calcifications in dense mammograms

This study attempts to determine whether intensity windowing (IW) improves detection of simulated calcifications in dense mammograms. Clusters of five simulated calcifications were embedded in dense mammograms digitized at 50-μm pixels, 12 bits deep. Film images with no windowing applied were compared with film images with nine different window widths and levels applied. A simulated cluster was embedded in a realistic background of dense breast tissue, with the position of the cluster varied. The key variables involved in each trial included the position of the cluster, contrast level of the cluster, and the IW settings applied to the image. Combining the ten IW conditions, four contrast levels and four quadrant positions gave 160 combinations. The trials were constructed by pairing 160 combinations of key variables with 160 backgrounds. The entire experiment consisted of 800 trials. Twenty student observers were asked to detect the quadrant of the image in which the mass was located. There was a statistically significant improvement in detection performance for clusters of calcifications when the window width was set at 1024 with a level of 3328, and when the window width was set at 1024 with a level of 3456. The selected IW settings should be tested in the clinic with digital mammograms to determine whether calcification detection performance can be improved.

A study of radiologists viewing multiple computed tomography examinations using an eyetracking device

Understanding the scan patterns radiologists use to view medical images is critical to the design of image viewing devices. In this study, and eyetracker, a device for recording eye and head movement, was used to determine the scan patterns during the interpretation of single and multiple computed tomographic (CT) examinations presented on a four-over-four viewbox. CT examinations were used because they represent complex viewing situations. In two separate studies, radiologists viewed patient folders containing single or multiple CT chest examinations and dictated a report. Eye movement was recorded with an eyetracker and video camera. After mounting the films in order, radiologists generally started with a sequential scan through the entire examination, followed by careful viewing of two to four clusters of three to six images, followed by dictation. These results indicate that a well designed radiology workstation should provide an image index, sufficient display area to simultaneously view 10 or more images, random and sequential movement through the examination, image comparison, and image marking.

Improving the Detection of Simulated Masses in Mammograms through Two Different Image-Processing Techniques

RATIONALE AND OBJECTIVES The purpose of this study was to determine whether contrast-limited adaptive histogram equalization (CLAHE) or histogram-based intensity windowing (HIW) improves the detection of simulated masses in dense mammograms. MATERIALS AND METHODS Simulated masses were embedded in portions of mammograms of patients with dense breasts; the mammograms were digitized at 50 microm per pixel, 12 bits deep. In two different experiments, images were printed both with no processing applied and with related parameter settings of two image-processing methods. A simulated mass was embedded in a realistic background of dense breast tissue, with its position varied. The key variables in each trial included the position of the mass, the contrast levels of the mass relative to the background, and the selected parameter settings for the image-processing method. RESULTS The success in detecting simulated masses on mammograms with dense backgrounds depended on the parameter settings of the algorithms used. The best HIW setting performed better than the best fixed-intensity window setting and better than no processing. Performance with the best CLAHE settings was no different from that with no processing. In the HIW experiment, there were no significant differences in observer performance between processing conditions for radiologists and nonradiologists. CONCLUSION HIW should be tested in clinical images to determine whether the detection of masses by radiologists can be improved. CLAHE processing will probably not improve the detection of masses on clinical mammograms.

Contrast Transmission In Medical Image Display

The display of medical images involves transforming recorded intensities such at CT numbers into perceivable intensities such as combinations of color and luminance. For the viewer to extract the most information about patterns of decreasing and increasing recorded intensity, the display designer must pay attention to three issues: 1) choice of display scale, including its discretization; 2) correction for variations in contrast sensitivity across the display scale due to the observer and the display device (producing an honest display); and 3) contrast enhancement based on the information in the recorded image and its importance, determined by viewing objectives. This paper will present concepts and approaches in all three of these areas. In choosing display scales three properties are important: sensitivity, associability, and naturalness of order. The unit of just noticeable difference (jnd) will be carefully defined. An observer experiment to measure the jnd values across a display scale will be specified. The overall sensitivity provided by a scale as measured in jnds gives a measure of sensitivity called the perceived dynamic range (PDR). Methods for determining the PDR fran the aforementioned PDR values, and PDRs for various grey and pseudocolor scales will be presented. Methods of achieving sensitivity while retaining associability and naturalness of order with pseudocolor scales will be suggested. For any display device and scale it is useful to compensate for the device and observer by preceding the device with an intensity mapping (lookup table) chosen so that perceived intensity is linear with display-driving intensity. This mapping can be determined from the aforementioned jnd values. With a linearized display it is possible to standardize display devices so that the same image displayed on different devices or scales (e.g. video and hard copy) will be in sane sense perceptually equivalent. Furthermore, with a linearized display, it is possible to design contrast enhancement mappings that optimize the transmission of information from the recorded image to the display-driving signal with the assurance that this information will not then be lost by a -further nonlinear relation between display-driving and perceived intensity. It is suggested that optimal contrast enhancement mappings are adaptive to the local distribution of recorded intensities.

Eye movement during computed tomography interpretation: Eyetracker results and image display-time implications

Stacked displays hold the potential for accurate interpretation of multiple computed tomography (CT) studies on a low-cost workstation. But can such a display scroll as quickly as radiologists can move their eyes to the next image on a film? To address this question, eye-movement duration during CT chest interpretation was recorded using an electronic eye tracker. Adjacent eye movements (±1 image in sequence) averaged 0.54 seconds. Time motion analysis indicates that a CT workstation using a stacked approach with a 0.2-second image display time and a simple interaction can display the next image in less than 0.4 seconds, so a stacked approach should allow a low-cost workstation to facilitate acceptable interpretation of multiple CT or magnetic resonance studies. However, nonadjacent eye movement is likely to take longer and radiologist behavior may be effected.

Contrast Perception With Video Displays

Distributed picture archiving and communication systems require electronic displays, today probably video displays. An obvious restriction with video displays, especially when multiple images are viewed, is on resolution both along image lines and due to the video raster. The effect of this restriction and the needs for improvement will be briefly reviewed. Perhaps a less obvious restriction of video displays is on contrast, as compared to film. Only limited grey-scale contrast is provided, and the fact that multiple images must be presented near each other on a single display means that the contents of one image will affect the perception of another. The perceptual and display mechanisms causing these effects will be described, means of specifying these contrast effects will be presented, and quantitative measures of the effectiveness of various display systems will be given. Pseudocolor scales provide a means on video displays of lessening the restriction on contrast. However, these scales bring with them problems of associability and variation in relative sensitivity across the scale. A linearization method will be presented for avoiding the second problem and thus allowing the comparison of different scales. Ppproachs for choosing sensitive pseudocolor scales without associability difficulties or contour artifacts will be presented, and specific scales superior to grey-scale will be recommended.