In this work, we demonstrate the ability to determine the material composition of a sample by measuring coherent scatter
diffraction patterns generated using a coded-aperture x-ray scatter imaging (CAXSI) system. Most materials are known
to exhibit unique diffraction patterns through coherent scattering of low-energy x-rays. However, clinical x-ray imagers
typically discard scatter radiation as noise that degrades image quality. Through the addition of a coded aperture, the
system can be sensitized to coherent scattered photons that carry information about the identity and location of the
scattering material. In this work, we demonstrate this process using a Monte-Carlo simulation of a CAXSI system. A
simulation of a CAXSI system was developed in GEANT4 with modified physics libraries to model coherent scatter
diffraction patterns in materials. Simulated images were generated from 10 materials including plastics, hydrocarbons,
and biological tissue. The materials were irradiated using collimated pencil- and fan-beams with energies of 160 kVp.
The diffraction patterns were imaged using a simulated 2D detector and mathematically deconstructed using an
analytical projection model that accounted for the known x-ray source spectrum. The deconstructed diffraction patterns
were then matched with a library of known coherent scatter form-factors of different materials to determine the identity
of the scatterer at different locations in the object. The results showed good agreement between the measured and known
scatter patterns from the materials, demonstrating the ability to image and identify materials at different 3D locations
within an object using a projection-based CAXSI system.
While diagnostic improvement via breast tomosynthesis has been notable, the full potential of tomosynthesis
has not yet been realized. This is because of the complex task of optimizing multiple parameters that constitute
image acquisition and thus affect tomosynthesis performance. Those parameters include dose, number of
angular projections, and the total angular span of those projections. In this study, we investigated the effects of
acquisition parameters, independent of each other, on the overall diagnostic image quality of tomosynthesis.
Five mastectomy specimens were imaged using a prototype tomosynthesis system. 25 angular projections of
each specimen were acquired at 6.2 times typical single-view mammographic dose level. Images at lower dose
levels were then simulated using a noise modification routine. Each projection image was supplemented with
84 simulated 3 mm 3D lesions embedded at the center of 84
non-overlapping ROIs. The projection images were
then reconstructed using a filtered-back projection (FBP) algorithm at 224 different combinations of acquisition
parameters to investigate which one of the many possible combinations maximized performance. Performance
was evaluated in terms of a Laguerre-Gauss channelized Hotelling observer model-based measure of lesion
detectability. Results showed that performance improved with an increase in the total acquisition dose level and
the angular span. At a constant dose level and angular span, the performance rolled-off beyond a certain number
of projections, indicating that simply increasing the number of projections in tomosynthesis may not necessarily
improve its performance. The best performance was obtained with 15-17 projections spanning an angular arc of
~45° - the maximum tested in our study, and for an acquisition dose equal to single-view mammography. The
optimization framework developed in this framework is applicable to other reconstruction techniques and other
multi-projection systems.
We are reporting the optimized acquisition scheme of multi-projection breast Correlation Imaging (CI)
technique, which was pioneered in our lab at Duke University. CI is similar to tomosynthesis in its image
acquisition scheme. However, instead of analyzing the reconstructed images, the projection images are directly
analyzed for pathology. Earlier, we presented an optimized data acquisition scheme for CI using mathematical
observer model. In this article, we are presenting a Computer Aided Detection (CADe)-based optimization
methodology. Towards that end, images from 106 subjects recruited for an ongoing clinical trial for
tomosynthesis were employed. For each patient, 25 angular projections of each breast were acquired. Projection
images were supplemented with a simulated 3 mm 3D lesion. Each projection was first processed by a
traditional CADe algorithm at high sensitivity, followed by a reduction of false positives by combining
geometrical correlation information available from the multiple images. Performance of the CI system was
determined in terms of free-response receiver operating characteristics (FROC) curves and the area under ROC
curves. For optimization, the components of acquisition such as the number of projections, and their angular
span were systematically changed to investigate which one of the many possible combinations maximized the
sensitivity and specificity. Results indicated that the performance of the CI system may be maximized with 7-11
projections spanning an angular arc of 44.8°, confirming our earlier findings using observer models. These
results indicate that an optimized CI system may potentially be an important diagnostic tool for improved breast
cancer detection.
The purpose of this project is to study two Computer Aided Detection (CADe) systems for breast masses for
digital tomosynthesis using reconstructed slices. This study used eighty human subject cases collected as part
of on-going clinical trials at Duke University. Raw projections images were used to identify suspicious regions
in the algorithm's high sensitivity, low specificity stage using a Difference of Gaussian filter. The filtered
images were thresholded to yield initial CADe hits that were then shifted and added to yield a 3D distribution
of suspicious regions. The initial system performance was 95% sensitivity at 10 false positives per breast
volume. Two CADe systems were developed. In system A, the central slice located at the centroid depth was
used to extract a 256 X 256 Regions of Interest (ROI) database centered at the lesion coordinates. For system B,
5 slices centered at the lesion coordinates were summed before the extraction of 256 × 256 ROIs. To avoid
issues associated with feature extraction, selection, and merging, information theory principles were used to
reduce false positives for both the systems resulting in a classifier performance of 0.81 and 0.865 Area Under
Curve (AUC) with leave-one-case-out sampling. This resulted in an overall system performance of 87%
sensitivity with 6.1 FPs/ volume and 85% sensitivity with 3.8 FPs/ volume for systems A and B respectively.
This system therefore has the potential to detect breast masses in tomosynthesis data sets.
Under typical dark conditions found in reading rooms, a reader's pupils will contract and dilate as the visual focus
intermittently shifts between the high luminance monitor and the darker background wall, resulting in increased visual
fatigue and the degradation of diagnostic performance. A controlled increase of ambient lighting may, however,
minimize these visual adjustments and potentially improve reader comfort and accuracy. This paper details results from
two psychophysical studies designed to determine the effect of a controlled ambient lighting increase on observer
detection of subtle objects and lesions viewed on a DICOM-calibrated medical-grade LCD. The first study examined the
effect of increased ambient lighting on detection of subtle objects embedded within a uniform background, while the
second study examined observer detection performance of subtle cancerous lesions in mammograms and chest
radiographs. In both studies, observers were presented with images under a dark room condition (1 lux) and an increased
room illuminance level (50 lux) for which the luminance level of the diffusely reflected light from the background wall
was approximately equal to that of the displayed image. The display was calibrated to an effective luminance ratio of
409 for both lighting conditions. Observer detection performance under each room illuminance condition was then
compared. Identification of subtle objects embedded within the uniform background improved from 59% to 67%, while
detection time decreased slightly with additional illuminance. An ROC analysis of the anatomical image results revealed
that observer AUC values remained constant while detection time decreased under increased illuminance. The results
provide evidence that an ambient lighting increase may be possible without compromising diagnostic efficacy.
Last year in this conference, we presented a theoretical analysis of how ambient lighting in dark reading rooms
could be moderately increased without compromising the interpretation of images displayed on LCDs. Based on
that analysis, in this paper we present results of two psychophysical experiments which were designed to verify
those theoretical predictions. The first experiment was designed to test how an increase in ambient lighting affects
the detection of subtle objects at different luminance levels, particularly at lower luminance levels. Towards that
end, images of targets consisting of low-contrast objects were shown to seven observers, first under a dark room
illumination condition of 1 lux and then under a higher room illumination condition of 50 lux. The targets had three
base luminance values of 1, 12 and 35 cd/m2 and were embedded in a uniform background. The uniform background
was set to 12 cd/m2 which enabled fixing Ladp, the visual adaptation luminance value when looking at the display,
to 12 cd/m2. This value also matched the luminance value of about 12 cd/m2 reflected off the wall surrounding the
LCD at the higher ambient lighting condition. The task of the observers was to detect and classify the displayed
objects under the two room lighting conditions. The results indicated that the detection rate in dark area (base
luminance of 1 cd/m2) increased by 15% when the ambient illumination is increased from 1 to 50 lux. The increase
was not conclusive for targets embedded in higher luminance regions, but there was no evidence to the contrary
either. The second experiment was designed to investigate the adaptation luminance value of the eye when viewing
typical mammograms. It was found that, for a typical display luminance calibration, this value might lie between 12
and 20 cd/m2. Findings from the two experiments provide justification for a controlled increase of ambient lighting
to improve ergonomic viewing conditions in darkly lit reading rooms while potentially improving diagnostic
performance.
KEYWORDS: Breast, Sensors, Mathematical modeling, Performance modeling, 3D modeling, Imaging systems, Digital breast tomosynthesis, Mammography, Image processing, Binary data
In this study, we used a mathematical observer model to combine information obtained from multiple angular projections of the same breast to determine the overall detection performance of a multi-projection breast imaging system in detectability of a simulated mass. 82 subjects participated in the study and 25 angular projections of each breast were acquired. Projections from a simulated 3 mm 3-D lesion were added to the projection images. The lesion was assumed to be embedded in the compressed breast at a distance of 3 cm from the detector. Hotelling observer with Laguerre-Gauss channels (LG CHO) was applied to each image. Detectability was analyzed in terms of ROC curves and the area under ROC curves (AUC). The critical question studied is how to best integrate the individual decision variables across multiple (correlated) views. Towards that end, three different methods were investigated. Specifically, 1) ROCs from different projections were simply averaged; 2) the test statistics from different projections were averaged; and 3) a Bayesian decision fusion rule was used. Finally, AUC of the combined ROC was used as a parameter to optimize the acquisition parameters to maximize the performance of the system. It was found that the Bayesian decision fusion technique performs better than the other two techniques and likely offers the best approximation of the diagnostic process. Furthermore, if the total dose level is held constant at 1/25th of dual-view mammographic screening dose, the highest detectability performance is observed when considering only two projections spread along an angular span of 11.4°.
The purpose of this study was to determine the effect of dose reduction on the detectability of breast lesions in mammograms. Mammograms with dose levels corresponding to 50% and 25% of the original clinically-relevant exposure levels were simulated. Detection of masses and microcalicifications embedded in these mammograms was analyzed by four mathematical observer models, namely, the Hotelling Observer, Non-prewhitening Matched Filter with Eye Filter (NPWE), and Laguerre-Gauss and Gabor Channelized Hotelling Observers. Performance was measured in terms of ROC curves and Area under ROC Curves (AUC) under Signal Known Exactly but Variable Tasks (SKEV) paradigm. Gabor Channelized Hotelling Observer predicted deterioration in detectability of benign masses. The other algorithmic observers, however, did not indicate statistically significant differences in the detectability of masses and microcalcifications with reduction in dose. Detection of microcalcifications was affected more than the detection of masses. Overall, the results indicate that there is a potential for reduction of radiation dose level in mammographic screening procedures without severely compromising the detectability of lesions.
Ambient lighting in soft-copy reading rooms are currently kept at low values to preserve contrast rendition in the dark regions of a medical image. Low illuminance levels, however, create inadequate viewing conditions and may also cause eye-strain. This eye-strain may be attributed to notable variations in luminance adaptation state of
the reader's eyes when moving the gaze intermittently between the brighter display and darker surrounding surfaces. This paper presents a methodology to optimize the lighting conditions of reading rooms to reduce visual fatigue by minimizing this variation by exploiting the properties of LCDs with low diffuse reflection coefficients and high
luminance ratio. First, a computational model was developed to determine a global luminance adaptation value, Ladp, when viewing a medical image on display. The model is based on the diameter of the pupil size which depends on the luminance of the observed object. Second, this value was compared with the luminance reflected off surrounding surfaces, Ls, under various conditions of room illuminance, E , different values of diffuse reflection
coefficients of surrounding surfaces, Rs, and calibration settings of a typical LCD. The results suggest that for
typical luminance settings of current LCDs, it is possible to raise ambient illumination to minimize differences in eye adaptation, potentially reducing visual fatigue while also complying with the TG18 specifications for controlled contrast rendition. Specifically, room illumination in the 75-150 lux range and surface diffuse reflection coefficients in the practical range of 0.13-0.22 sr-1 provide an ideal setup for typical LCDs. Furthermore, displays with lower
diffuse reflectivity and with higher inherent luminance ratio than currently possible in most LCDs can potentially
help further decrease eye fatigue, providing an improved ergonomic viewing conditions in reading rooms.
The use of flat panel detectors in computed tomography (CT) systems can improve resolution, reduce system cost, and add operational flexibility by combining fluoroscopy and radiography applications within CT systems. However, some prior studies have suggested that flat panel detectors would not perform well in CT applications due to their lack of high dynamic range, lag artifacts, and inadequate frame rate. The purpose of this study was to perform a physical evaluation of a prototype flat panel detector capable of high frame rates and extended dynamic range. The flat panel detector used had a pixel size of 194 microns and a matrix size of 2048x1536. The detector could be configured for several combinations of frame rate and matrix size up to 750 frames per second for a 512x16 matrix size with 4x4 binning. The evaluation was performed in terms of the MTF and DQE as a function of frame rate and exposure at the IEC RQA5 (~75 kVp, 21 mm Al) beam quality. The image lag was evaluated in terms of temporal-frequency dependent transfer function. Offset shift were also evaluated. Preliminary results indicate 0.1 MTF at 0.92 cycles/mm and DQE(0) of approximately 0.8, 0.6, 0.4, and 0.22 at 0.144, 0.065, 0.035, and 0.008 mR per frame exposures. The temporal MTF exhibited a low-frequency drop and a value of 0.5 at the Nyquist frequency. Offset shift was negligible. Considering high frame rate capabilities of the new detector, the results suggest that the detector has potential for use in real-time CT applications including CT angiography.
This paper discusses the issue of calibration for the growing number of electronic displays used in the filmless and electronic radiology departments. It concentrates on CRT and LCD displays as these are the most matured electronic display systems available at this time. It is shown that grayscale calibration is necessary and useful to optimally display the information contained in the various digital images in diagnostic radiology. In addition properties and drawbacks of four prevalent standards for display function have been discussed.
Four methods for near real-time measurement of the modulation transfer function (MTF) of electronic displays are presented. The methods are based on measuring the display’s response to an edge, periodic bar-patterns, line and whitenoise stimuli. Although all the methods yield practically the same result, they require different data acquisition time and different degrees of human intervention while analyzing the acquired data. The paper presents a comparison between the four methods in context of the time required to implement each and cites implementation issues that need to be addressed in order to achieve real time data analysis and presentation.
The paper presents methodologies for characterizing liquid crystal displays (LCDs) and the image quality of two new high-performance monochrome LCDs, a 2- and a 5-million-pixel display. The systems' image quality is described by on-axis characteristic curves, luminance range and contrast, luminance and contrast as a function of viewing angle, diffuse and specular reflection coefficients, color coordinates, luminance uniformity across the display screen, temporal response time and temporal modulation transfer function (MTF), spatial MTF, spatial noise power spectra and signal-to-noise ratios.
The LCDs are equipped with an internal photosensor that maintains a desired maximum luminance and calibration to a given display function. The systems offer aperture and temporal modulation to place luminance levels with more than 12-bit precision on a desired display function and achieve very uniform contrast distribution over the luminance range. The LCDs have image quality that is superior in many respects to high-performance and high-resolution cathode-ray-tube (CRT) displays, except for the temporal MTF and the spatial noise. Spatial noise appears to be comparable to CRT display systems with P4 or P104 phosphor screens.
This paper presents the results of initial physical and psycho-physical evaluations of the noise of high resolution LCDs. 5 LCDs were involved, having 4 different pixel structures. Spatial as well as temporal noise was physically measured with the aid of a high-performance CCD camera. Human contrast sensitivity in the presence of spatial noise was determined psycho-physically using periodic stimuli (square-wave patterns) as well as aperiodic stimuli (squares). For the measurements of the human contrast sensitivity, all LCDs were calibrated to the DICOM 14 Grayscale Standard Display Function (GSDF). The results demonstrate that spatial noise is the dominant noise in all LCDs, while temporal noise is insignificant and plays only a minor part. The magnitude of spatial noise of LCDs is in the range between that of CRTs with a P104 and that of CRTs with a P45. Of particular importance with respect to LCD noise is the contribution of the pixel structure to the Noise Power Spectrum, which shows up as sharp spikes at spatial frequencies beyond the LCDs’ Nyquist frequency. The paper does not offer any clues about the importance of these spikes on the human contrast sensitivity.
This paper discusses display parameters such as display function, contrast, dynamic range, veiling glare and spatial resolution of displays useful in digital radiology. After a review of the traditional display in diagnostic radiology, namely the film-lightbox, based on the film-screen combination, the paper concentrates on the Active Matrix Liquid Crystal Flat Panel Display (AM-LCD). The AM-LCD will most likely mature and may become the display of choice in the near future, replacing the Cathode Ray Tube Display (CRT), which is presently the dominating softcopy display. A comparison between pertinent performance characteristics of AM-LCD and CRT demonstrates that spatial resolution (Modulation Transfer Function or MTF) and veiling glare for the AM-LCD are already superior to those of the CRT.
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