A dual-energy subtraction technique for microcalcification imaging in digital mammography--a signal-to-noise analysis

Breast cancer may manifest as microcalcifications (microCs) in x-ray mammography. However, the detection and visualization of microCs are often obscured by the overlapping tissue structures. The dual-energy subtraction imaging technique offers an alternative approach for imaging and visualizing microCs. With this technique, separate high- and low-energy images are acquired and their differences are used to "cancel" out the background tissue structures. However, the subtraction process could increase the statistical noise level relative to the calcification contrast. Therefore, a key issue with the dual-energy subtraction imaging technique is to weigh the benefit of removing the cluttered background tissue structure over the drawback of reduced signal-to-noise ratio in the subtracted microC images. In this report, a theoretical framework for calculating the (quantum) noise in the subtraction images is developed and the numerical computations are described. We estimate the noise levels in the dual-energy subtraction signals under various imaging conditions, including the x-ray spectra, microC size, tissue composition, and breast thickness. The selection of imaging parameters is optimized to evaluate the feasibility of using a dual-energy subtraction technique for the improved detection and visualization of microCs. We present the results and discuss its dependence on imaging parameters.     

Dual-energy subtraction mammography

Dual-energy subtraction mammography was performed for breast examinations. To obtain a dual-energy subtraction image with a digital radiography unit, high- and low-energy images were obtained at an appropriate time interval under different x-ray exposure conditions. In about 50% of the patients with breast cancer included in this study, we obtained better diagnostic accuracy with dual-energy subtraction images than with conventional mammography. In some cases of breast cancer, it was possible to diagnose intraductal spread of this lesion on the subtracted images. Furthermore, abnormal lesions commonly observed on mammography in cases of fibrocystic disease tended to be erased on subtracted images. Thus, dual-energy subtraction mammography provided useful information for diagnosing breast diseases. However, there were several cases in which the subtracted images lacked sufficient image quality, and several technical problems with subtraction are thought to remain.     

Dual-energy approach to contrast-enhanced mammography using the balanced filter method: spectral optimization and preliminary phantom measurement

Dual-energy contrast agent-enhanced mammography is a technique of demonstrating breast cancers obscured by a cluttered background resulting from the contrast between soft tissues in the breast. The technique has usually been implemented by exploiting two exposures to different x-ray tube voltages. In this article, another dual-energy approach using the balanced filter method without switching the tube voltages is described. For the spectral optimization of dual-energy mammography using the balanced filters, we applied a theoretical framework reported by Lemacks et al. [Med. Phys. 29, 1739-1751 (2002)] to calculate the signal-to-noise ratio (SNR) in an iodinated contrast agent subtraction image. This permits the selection of beam parameters such as tube voltage and balanced filter material, and the optimization of the latter's thickness with respect to some critical quantity-in this case, mean glandular dose. For an imaging system with a 0.1 mm thick CsI:T1 scintillator, we predict that the optimal tube voltage would be 45 kVp for a tungsten anode using zirconium, iodine, and neodymium balanced filters. A mean glandular dose of 1.0 mGy is required to obtain an SNR of 5 in order to detect 1.0 mg/cm2 iodine in the resulting clutter-free image of a 5 cm thick breast composed of 50% adipose and 50% glandular tissue. In addition to spectral optimization, we carried out phantom measurements to demonstrate the present dual-energy approach for obtaining a clutter-free image, which preferentially shows iodine, of a breast phantom comprising three major components-acrylic spheres, olive oil, and an iodinated contrast agent. The detection of iodine details on the cluttered background originating from the contrast between acrylic spheres and olive oil is analogous to the task of distinguishing contrast agents in a mixture of glandular and adipose tissues.     

A correlated noise reduction algorithm for dual-energy digital subtraction angiography

It has long been recognized that the problems of motion artifacts in conventional time subtraction digital subtraction angiography (DSA) may be overcome using energy subtraction techniques. Of the variety of energy subtraction techniques investigated, non-k-edge dual-energy subtraction offers the best signal-to-noise ratio (SNR). However, this technique achieves only 55% of the temporal DSA SNR. Noise reduction techniques that average the noisier high-energy image produce various degrees of noise improvement while minimally affecting iodine contrast and resolution. A more significant improvement in dual-energy DSA iodine SNR, however, results when the correlated noise that exists in material specific images is appropriately cancelled. The correlated noise reduction (CNR) algorithm presented here follows directly from the dual-energy computed tomography work of Kalender who made explicit use of noise correlations in material specific images to reduce noise. The results are identical to those achieved using a linear version of the two-stage filtering process described by Macovski in which the selective image is filtered to reduce high-frequency noise and added to a weighted, high SNR, nonselective image which has been processed with a high-frequency bandpass filter. The dual-energy DSA CNR algorithm presented here combines selective tissue and iodine images to produce a significant increase in the iodine SNR while fully preserving iodine spatial resolution. Theoretical calculations predict a factor of 2-4 improvement in SNR compared to conventional dual-energy images. The improvement factor achieved is dependent upon the x-ray beam spectra and the size of blurring kernel used in the algorithm.(ABSTRACT TRUNCATED AT 250 WORDS)     

Theoretical optimization of dual-energy x-ray imaging with application to mammography

Detection of a target object in a radiological image is often impeded by an obscuring background "clutter" resulting from the contrast between various materials in the neighborhood of the target. Dual-energy techniques can reduce or remove this clutter. In order for the target to be detectable in the image after dual-energy processing, the signal-to-noise ratio (SNR), defined as the difference between the target and the background divided by the photon noise in the difference, must exceed some threshold. A given SNR may be obtained for a wide range of the energies of the two x-ray beams and the ratio of their fluences. A theoretical model is developed which permits the choice of beams to be optimized with respect to some critical parameter--in this case, patient dose. The analysis is applied to the detection of calcifications in mammography. For an ideal imaging system, we predict that the optimum beam energies are 19 and 68 keV. A dose of 0.42 cGy is required to obtain an SNR of 5 for detection of a 0.02-cm cubic calcification in the resulting clutter-free image. This can be reduced to 0.16 cGy if the higher energy image is smoothed, prior to dual-energy processing, such that its variance is reduced to one-fourth of its unsmoothed value.     

Temporal subtraction of dual-energy chest radiographs

Temporal subtraction and dual-energy imaging are two enhanced radiography techniques that are receiving increased attention in chest radiography. Temporal subtraction is an image processing technique that facilitates the visualization of pathologic change across serial chest radiographic images acquired from the same patient; dual-energy imaging exploits the differential relative attenuation of x-ray photons exhibited by soft-tissue and bony structures at different x-ray energies to generate a pair of images that accentuate those structures. Although temporal subtraction images provide a powerful mechanism for enhancing visualization of subtle change, misregistration artifacts in these images can mimic or obscure abnormalities. The purpose of this study was to evaluate whether dual-energy imaging could improve the quality of temporal subtraction images. Temporal subtraction images were generated from 100 pairs of temporally sequential standard radiographic chest images and from the corresponding 100 pairs of dual-energy, soft-tissue radiographic images. The registration accuracy demonstrated in the resulting temporal subtraction images was evaluated subjectively by two radiologists. The registration accuracy of the soft-tissue-based temporal subtraction images was rated superior to that of the conventional temporal subtraction images. Registration accuracy also was evaluated objectively through an automated method, which achieved an area-under-the-ROC-curve value of 0.92 in the distinction between temporal subtraction images that demonstrated clinically acceptable and clinically unacceptable registration accuracy. By combining dual-energy soft-tissue images with temporal subtraction, misregistration artifacts can be reduced and superior image quality can be obtained.     

Dual-energy mammography: simulation studies

This paper presents a mammography simulator and demonstrates its applicability in feasibility studies in dual-energy (DE) subtraction mammography. This mammography simulator is an evolution of a previously presented x-ray imaging simulation system, which has been extended with new functionalities that are specific for DE simulations. The new features include incident exposure and dose calculations, the implementation of a DE subtraction algorithm as well as amendments to the detector and source modelling. The system was then verified by simulating experiments and comparing their results against published data. The simulator was used to carry out a feasibility study of the applicability of DE techniques in mammography, and more precisely to examine whether this modality could result in better visualization and detection of microcalcifications. Investigations were carried out using a 3D breast software phantom of average thickness, monoenergetic and polyenergetic beam spectra and various detector configurations. Dual-shot techniques were simulated. Results showed the advantage of using monoenergetic in comparison with polyenergetic beams. Optimization studies with monochromatic sources were carried out to obtain the optimal low and high incident energies, based on the assessment of the figure of merit of the simulated microcalcifications in the subtracted images. The results of the simulation study with the optimal energies demonstrated that the use of the DE technique can improve visualization and increase detectability, allowing identification of microcalcifications of sizes as small as 200 microm. The quantitative results are also verified by means of a visual inspection of the synthetic images.     

Signal-to-noise ratio evaluation in dual-energy radiography with synchrotron radiation

Dual-energy radiography is an effective technique that allows removal of contrast between pairs of materials in order to display details of interest on a uniform background. In mammographic images the detection of small nodules is often impeded by obscuring background 'clutter' resulting from the contrast between normal tissues (glandular and adipose) in their neighbourhood. We consider whether it could be possible to apply dual-energy radiography to the breast, which is hypothetically principally composed of three tissues, glandular, adipose and cancerous, in order to remove the contrast due to the distribution of normal tissues and, as a consequence, to enhance the intrinsic contrast of the pathology. The purpose of this work is to test the limitations of dual-energy radiography on a three-component phantom under optimum conditions of the source and detector. We use a synchrotron monochromatic beam, produced at the ELETTRA synchrotron facility (Trieste, Italy), and an imaging plate detector, in order to acquire two images at low and high energies of a phantom composed of polyethylene, plexiglas and water. For evaluation of the potential of this procedure we studied the signal-to-noise ratio (SNR) of polyethylene and water on a set of images obtained by applying the dual-energy procedure. We found that the SNR of polyethylene and water is around the detectability threshold (according to Rose's criteria) at the contrast cancellation angles. Finally we evaluated the air entrance dose required for this double exposure, resulting in 0.81 mGy for the low-energy image and 0.01 mGy for the high-energy image. To obtain the same image quality for a standard breast of 5.5 cm, mean glandular doses of 3.50 mGy and 0.03 mGy at 17 keV and at 34 keV, respectively, are required.     

Imaging properties of digital magnification radiography

Flat panel detectors exhibit improved signal-to-noise ratio (SNR) and display capabilities compared to film. This improvement necessitates a new evaluation of optimal geometry for conventional projection imaging applications such as digital projection mammography as well as for advanced x-ray imaging applications including cone-beam computed tomography (CT), tomosynthesis, and mammotomography. Such an evaluation was undertaken in this study to examine the effects of x-ray source distribution, inherent detector resolution, magnification, scatter rejection, and noise characteristics including noise aliasing. A model for x-ray image acquisition was used to develop generic results applicable to flat panel detectors with similar x-ray absorption characteristics. The model assumed a Gaussian distribution for the focal spot and a rectangular distribution for a pixel. A generic model for the modulated transfer function (MTF) of indirect flat panel detectors was derived by a nonlinear fit of empirical receptor data to the Burgess model for phosphor MTFs. Noise characteristics were investigated using a generic noise power spectrum (NPS) model for indirect phosphor-based detectors. The detective quantum efficiency (DQE) was then calculated from the MTF and NPS models. The results were examined as a function of focal spot size (0.1, 0.3, and 0.6 mm) and pixel size (50, 100, 150, and 200 microm) for magnification ranges 1 to 3. Mammography, general radiography (also applicable to mammotomography), and chest radiography applications were explored using x-ray energies of 28, 74, and 120 kVp, respectively. Nodule detection was examined using the effective point source scatter model, effective DQE, and the Hotelling SNR2 efficiency. Results indicate that magnification can potentially improve the signal and noise performance of digital images. Results also show that a cross over point occurs in the spatial frequency above and below which the effects of magnification differ indicating that there are task dependent tradeoffs associated with magnification. The cross over point varies depending upon focal spot size, pixel size, x-ray energy, and source-to-image-distance (SID). For mammography, the cross over point occurs for a 0.3 mm focal spot while a 0.6 mm focal spot indicates that magnification does not improve image quality due to focal spot blurring. Thus, the benefit of magnification may be limited. For general radiography (as well as mammotomography), and chest radiography, the cross over point changes with SID. For a system with a 0.3 mm focal spot, 100 microm pixel size, a 2 m SID, and the applicable tissue thickness and scatter components, optimal magnification improved SNR2 by approximately 1.2 times for mammography and 1.5 times for general radiography (and mammotomography). These results indicate that the optimal geometry can improve image quality without changing patient dose or otherwise reduce dose without compromising image quality.     

Comparison of three different techniques for dual-energy subtraction imaging in digital radiography: A signal-to-noise analysis

Dual-energy subtraction imaging techniques allow the tissue and bone structures in the patient to be visualized and studied in two separate images, thus removing the obscurity associated with overlapping of the two structures. In addition, they allow the subtraction image signals to be used for quantifying the tissue and bone thicknesses. Thus, capability for dual-energy subtraction imaging is often incorporated with new digital radiography systems. There are three different approaches to dual-energy image subtraction imaging techniques. Among them, the dual-kilovolt (peak) [kV(p)] and sandwich detector techniques have been two widely used approaches. A third approach is the single-kV(p) dual-filter technique, which allows some flexible control of the spectra while avoiding the technical complexity of kV(p) value switching in slit-scan imaging. In this report, the noise properties associated with these three techniques are studied and compared by computing the noise variances in the subtraction image signals as a function of the kV(p) values and filter thicknesses. It was found that the dual-kVp technique results in the least noisy subtraction images, whereas the dual-filter technique results in slightly less noisy subtraction images than the sandwich detector technique. Following optimization of the kV(p) value and filter thicknesses, the dual-filter and sandwich detector techniques result in a noise level of approximately three and four times higher than that resulted from the dual-kV(p) technique, respectively.     

Dynamic dual-energy chest radiography: a potential tool for lung tissue motion monitoring and kinetic study

Dual-energy chest radiography has the potential to provide better diagnosis of lung disease by removing the bone signal from the image. Dynamic dual-energy radiography is now possible with the introduction of digital flat-panel detectors. The purpose of this study is to evaluate the feasibility of using dynamic dual-energy chest radiography for functional lung imaging and tumor motion assessment. The dual-energy system used in this study can acquire up to 15 frames of dual-energy images per second. A swine animal model was mechanically ventilated and imaged using the dual-energy system. Sequences of soft-tissue images were obtained using dual-energy subtraction. Time subtracted soft-tissue images were shown to be able to provide information on regional ventilation. Motion tracking of a lung anatomic feature (a branch of pulmonary artery) was performed based on an image cross-correlation algorithm. The tracking precision was found to be better than 1 mm. An adaptive correlation model was established between the above tracked motion and an external surrogate signal (temperature within the tracheal tube). This model is used to predict lung feature motion using the continuous surrogate signal and low frame rate dual-energy images (0.1-3.0 frames per second). The average RMS error of the prediction was (1.1 ± 0.3) mm. The dynamic dual energy was shown to be potentially useful for lung functional imaging such as regional ventilation and kinetic studies. It can also be used for lung tumor motion assessment and prediction during radiation therapy.     

图像融合技术在Computed Radiography影像中的应用研究

将图像融合技术应用于CR(ComputedRadiography)技术中 ,有效改善影像的信噪比 (signal-to -noiseratio)。运用双IP(ImagePlate)技术采集人体体模影像后 ,在变换域进行图像配准。建立融合图像的数学模型 ,基于此模型对配准完成的源图像实施不同权重的加权计算得到融合图像。结果　融合图像信噪比源图像可提高 30 %左右。结论　将图像融合技术应用于CR技术可有效改善影像质量 ,有助于提高诊断的准确性。     

Detection of single and clustered microcalcifications in mammograms using fractals models and neural networks

Microcalcifications (microCas) are often early signs of breast cancer. However, detecting them is a difficult visual task and recognizing malignant lesions is a complex diagnostic problem. In recent years, several research groups have been working to develop computer-aided diagnosis (CAD) systems for X-ray mammography. In this paper, we propose a method to detect and classify microcalcifications. In order to discover the presence of microCas clusters, particular attention is paid to the analysis of the spatial arrangement of detected lesions. A fractal model has been used to describe the mammographic image, thus, allowing the use of a matched filtering stage to enhance microcalcifications against the background. A region growing algorithm, coupled with a neural classifier, detects existing lesions. Subsequently, a second fractal model is used to analyze their spatial arrangement so that the presence of microcalcification clusters can be detected and classified. Reported results indicate that fractal models provide an adequate framework for medical image processing; consequently high correct classification rates are achieved.     

Noise reduction methods for hybrid subtraction

In digital subtraction angiography, hybrid subtraction provides selective vessel images free of soft-tissue motion artifacts but with a lower signal-to-noise ratio (SNR) than temporal subtraction images. An image processing method called measurement-dependent filtering has been developed to enhance the SNR of hybrid images without losing resolution or selectivity. Linear combinations of four images consisting of a pre- and postcontrast dual-energy measurement pair form both the hybrid image and a lower noise but less selective vessel image. The noise-reduced image is derived by combining the low-frequency components of the hybrid image with the high-frequency components of the lower noise image in a variety of ways. The results of the filtering method, when tested on both phantom and clinical data, display images with about the same degree of conspicuity as the hybrid image and a SNR approaching that of the temporal image.     

Role of equalisation mammography of dense breasts

Parenchymal patterns characteristic of dense breasts are known to degrade the mammographic detection of small breast cancers and microcalcifications. This arises from large variations in exposure of the film, resulting in reduced image contrast over areas of suboptimal exposure. Based on sensitometric measurements of mammograms from a typical patient population, it is shown that over 60% of a typical mammogram in Wolfe's DY classification was found to be exposed suboptimally, suggesting a significant margin for improving mammography for these patients. In order to address this problem, a prototype mammographic version of scanning equalisation radiography (MSER) has been developed, which delivers a patient-specific spatially non-uniform distribution of breast exposure, adjusted to maintain optimal film exposure and contrast over the entire mammogram. Anthropomorphic phantom MSER images show a marked improvement in subjective image quality relative to conventional mammograms, while exhibiting a similar radiation risk. The detection of small microcalcifications and fibrils over clinically significant breast densities is found to be improved by factors eight and four, respectively. Such a system may be clinically practical through the use of multiple-beam equalisation methods with available X-ray tube technology.     

A dual-energy technique for enhanced localization accuracy in intracavitary brachytherapy

The orthogonal imaging method is commonly used for source localization in brachytherapy. In some cases, however, difficulty is encountered in determining the dummy sources because of the presence of either contrast materials or bony structures. We here offer a novel method for source localization utilizing a dual-energy, radiographic technique. In this approach, two sets of orthogonal radiographic images (anterior-posterior and lateral views) are obtained using two different x-ray energies. Image processing (i.e., subtraction between two image sets) is carried out to enhance the source image. In a study performed using a laboratory developed pelvic phantom, it was demonstrated that the dual-energy method could significantly enhance the image quality of the dummy sources, and improve the achievable precision and relative accuracy in localization of source positions. When directly combined with digital imaging modalities, the dual-energy method can be a useful technique to improve the accuracy in brachytherapy source localization from planar radiographs.     

Dual-energy digital mammography for calcification imaging: scatter and nonuniformity corrections

Mammographic images of small calcifications, which are often the earliest signs of breast cancer, can be obscured by overlapping fibroglandular tissue. We have developed and implemented a dual-energy digital mammography (DEDM) technique for calcification imaging under full-field imaging conditions using a commercially available aSi:H/CsI:Tl flat-panel based digital mammography system. The low- and high-energy images were combined using a nonlinear mapping function to cancel the tissue structures and generate the dual-energy (DE) calcification images. The total entrance-skin exposure and mean-glandular dose from the low- and high-energy images were constrained so that they were similar to screening-examination levels. To evaluate the DE calcification image, we designed a phantom using calcium carbonate crystals to simulate calcifications of various sizes (212-425 microm) overlaid with breast-tissue-equivalent material 5 cm thick with a continuously varying glandular-tissue ratio from 0% to 100%. We report on the effects of scatter radiation and nonuniformity in x-ray intensity and detector response on the DE calcification images. The nonuniformity was corrected by normalizing the low- and high-energy images with full-field reference images. Correction of scatter in the low- and high-energy images significantly reduced the background signal in the DE calcification image. Under the current implementation of DEDM, utilizing the mammography system and dose level tested, calcifications in the 300-355 microm size range were clearly visible in DE calcification images. Calcification threshold sizes decreased to the 250-280 microm size range when the visibility criteria were lowered to barely visible. Calcifications smaller than approximately 250 microm were usually not visible in most cases. The visibility of calcifications with our DEDM imaging technique was limited by quantum noise, not system noise.     

Studies of performance of antiscatter grids in digital radiography: effect on signal-to-noise ratio

We developed a theoretical model which describes the improvement of signal-to-noise ratio (SNR) by a grid in digital radiography. The model takes into account the effects of spatial variations in the scatter-to-primary ratio and in the large-area contrast over an image with structured background on quantum noise, and the effects of noise in the imaging system such as electronic noise and digitization noise. Based on the theoretical model, we analyzed the effects of these factors on the SNR when a grid is employed. We performed experimental measurements to evaluate the improvement in the SNR by a grid when quantum noise is the dominant noise source. It was found that the measured SNR improvement factor due to quantum noise agreed closely with that determined from the measured transmission values of a grid, as predicted from our theoretical model. In order to evaluate the relative performance of grids with various geometric design parameters for digital radiographic systems, we employed Monte Carlo calculations and determined the transmission values of a number of grids under various scatter conditions. The calculated SNR improvement factor, due to quantum noise, correlated well with the measured improvement of the SNR by the grids. Our model predicts that the SNR improvement factor depends strongly on the local contrast ratio and also on the scatter-to-primary ratio. The SNR improvement factor is higher in the underpenetrated regions than in the well-penetrated regions of an image.     

Comparison of clinical and physical measures of image quality in chest and pelvis computed radiography at different tube voltages

The aim of this work was to study the dependence of image quality in digital chest and pelvis radiography on tube voltage, and to explore correlations between clinical and physical measures of image quality. The effect on image quality of tube voltage in these two examinations was assessed using two methods. The first method relies on radiologists' observations of images of an anthropomorphic phantom, and the second method was based on computer modeling of the imaging system using an anthropomorphic voxel phantom. The tube voltage was varied within a broad range (50-150 kV), including those values typically used with screen-film radiography. The tube charge was altered so that the same effective dose was achieved for each projection. Two x-ray units were employed using a computed radiography (CR) image detector with standard tube filtration and antiscatter device. Clinical image quality was assessed by a group of radiologists using a visual grading analysis (VGA) technique based on the revised CEC image criteria. Physical image quality was derived from a Monte Carlo computer model in terms of the signal-to-noise ratio, SNR, of anatomical structures corresponding to the image criteria. Both the VGAS (visual grading analysis score) and SNR decrease with increasing tube voltage in both chest PA and pelvis AP examinations, indicating superior performance if lower tube voltages are employed. Hence, a positive correlation between clinical and physical measures of image quality was found. The pros and cons of using lower tube voltages with CR digital radiography than typically used in analog screen-film radiography are discussed, as well as the relevance of using VGAS and quantum-noise SNR as measures of image quality in pelvis and chest radiography.     

Dual-energy digital mammography for calcification imaging: noise reduction techniques

We have previously developed a dual-energy digital mammography (DEDM) technique for calcification imaging under full-field imaging conditions using a commercially available flat-panel based digital mammography system. Although dual-energy (DE) imaging could suppress the obscuration of calcifications by tissue-structure background, it also increases the intrinsic noise in the DE images. Here we report on the effects of three different noise reduction techniques on DE calcification images: a simple smoothing (boxcar) filter applied to the DE image, a median filter applied to the HE image prior to the computation of the DE image and an adaptation of the Kalender's correlated-noise reduction (KNR) technique for DEDM. We compared the different noise reduction techniques by evaluating their effects on DE calcification images of a 5 cm thick breast-tissue-equivalent slab with continuously varying glandular-tissue ratio superimposed with calcium carbonate crystals of various sizes that simulate calcifications. Evaluations of different noise reducing techniques were performed by comparison of the root-mean-square signal in background regions (no calcifications present) of the DE calcification images and the contrast-to-noise ratios (CNR) of the calcifications in the DE calcification images. Amongst the different noise reduction techniques evaluated in this study, the KNR method was found to be most effective in reducing the image noise and increasing the calcification visibility (or CNR), closely followed by the HE median filter technique. Although the simple smoothing (boxcar) filter reduced the noise, it did not improve calcification visibility. The visible calcification threshold size with DEDM over smoothly varying background at screening mammography doses, assuming a CNR threshold of 4, was estimated to be around 250 microm with both the HE median filter and the KNR techniques. The quality of DE images with noise reduction techniques based on phantom studies were verified with DE images of an animal-tissue phantom that consisted of calcifications superimposed over more realistic tissue structures.