Digital radiography enhancement by nonlinear multiscale processing

X-ray dark-field chest radiography: a reader study to evaluate the diagnostic quality of attenuation chest X-rays from a dual-contrast scanning prototype

OBJECTIVES

To compare the visibility of anatomical structures and overall quality of the attenuation images obtained with a dark-field X-ray radiography prototype with those from a commercial radiography system.

METHODS

Each of the 65 patients recruited for this study obtained a thorax radiograph at the prototype and a reference radiograph at the commercial system. Five radiologists independently assessed the visibility of anatomical structures, the level of motion artifacts, and the overall image quality of all attenuation images on a five-point scale, with 5 points being the highest rating. The average scores were compared between the two image types. The differences were evaluated using an area under the curve (AUC) based z-test with a significance level of p ≤ 0.05. To assess the variability among the images, the distributions of the average scores per image were compared between the systems.

RESULTS

The overall image quality was rated high for both devices, 4.2 for the prototype and 4.6 for the commercial system. The rating scores varied only slightly between both image types, especially for structures relevant to lung assessment, where the images from the commercial system were graded slightly higher. The differences were statistically significant for all criteria except for the bronchial structures, the cardiophrenic recess, and the carina.

CONCLUSIONS

The attenuation images acquired with the prototype were assigned a high diagnostic quality despite a lower resolution and the presence of motion artifacts. Thus, the attenuation-based radiographs from the prototype can be used for diagnosis, eliminating the need for an additional conventional radiograph.

KEY POINTS

• Despite a low tube voltage (70 kVp) and comparably long acquisition time, the attenuation images from the dark-field chest radiography system achieved diagnostic quality for lung assessment. • Commercial chest radiographs obtained a mean rating score regarding their diagnostic quality of 4.6 out of 5, and the grating-based images had a slightly lower mean rating score of 4.2 out of 5. • The difference in rating scores for anatomical structures relevant to lung assessment is below 5%.

A New X-ray Medical-Image-Enhancement Method Based on Multiscale Shannon-Cosine Wavelet

Because of noise interference, improper exposure, and the over thickness of human tissues, the detailed information of DR (digital radiography) images can be masked, including unclear edges and reduced contrast. An image-enhancement algorithm based on wavelet multiscale decomposition is proposed to address the shortcomings of existing single-scale image-enhancement algorithms. The proposed algorithm is based on Shannon-Cosine wavelets by taking advantage of the interpolation, smoothness, tight support, and normalization properties. Next a multiscale interpolation wavelet operator is constructed to divide the image into several sub-images from high frequency to low frequency, and to perform different multi-scale wavelet transforms on the detailed image of each channel. So that the most subtle and diagnostically useful information in the image can be effectively enhanced. Moreover, the image will not be over-enhanced and combined with the high contrast sensitivity of the human eye's visual system in smooth regions, different attenuation coefficients are used for different regions to achieve the purpose of suppressing noise while enhancing details. The results obtained by some simulations show that this method can effectively eliminate the noise in the DR image, and the enhanced DR image detail information is clearer than before while having high effectiveness and robustness.

Advances in multiscale image processing and its effects on image quality in skeletal radiography

Multi-frequency processing (MFP) leads to enhanced image quality (IQ) of radiographs. This study is to determine the effect of third generation MFP (M3) on IQ in comparison to standard second-generation MFP (M2). 20 cadavers were examined and post-processing of radiographs was performed with both M2 and M3. Three readers blinded to the MFP used for each image independently compared corresponding image pairs according to overall IQ and depiction of bony structures and soft tissue (+ 2: notably better > 0: equal > - 2: notably worse). A significant deviation of the median grade from grade 0 (equal) (p < 0.01) for each evaluator A, B and C speaks against an equal image quality of M2- and M3-images. M3-images were categorized with better grades (+ 1, + 2) in 87.7% for overall image quality, in 90.4% for soft tissue and 81.8% for bony structures. M3 images showed significant higher averaged SNR and CNR for all investigated lower extremities than that of M2 images (0.031 < p < 0.049). The newest generation of MFP leads to significantly better depiction of anatomical structures and overall image quality than in images processed with the preceding generation of MFP. This provides increased diagnostic accuracy and further decreased radiation exposure.

Towards clinical grating-interferometry mammography

OBJECTIVES

Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, as several research works have demonstrated in a pre-clinical setting, since it is able to provide attenuation, differential phase contrast, and scattering images simultaneously. In order to translate this technique to the clinics, it has to be adapted to cover a large field-of-view within a clinically acceptable exposure time and radiation dose.

METHODS

We set up a grating interferometer that fits into a standard mammography system and fulfilled the aforementioned conditions. Here, we present the first mastectomy images acquired with this experimental device.

RESULTS AND CONCLUSION

Our system performs at a mean glandular dose of 1.6 mGy for a 5-cm-thick, 18%-dense breast, and a field-of-view of 26 × 21 cm2. It seems to be well-suited as basis for a clinical-environment device. Further, dark-field signals seem to support an improved lesion visualization. Evidently, the effective impact of such indications must be evaluated and quantified within the context of a proper reader study.

KEY POINTS

• Grating-interferometry-based mammography (GIM) might facilitate breast cancer detection, since it is sensitive to refraction and scattering and thus provides additional tissue information. • The most straightforward way to do grating-interferometry in the clinics is to modify a standard mammography device. • In a first approximation, the doses given with this technique seem to be similar to those of conventional mammography.

Radiation dose reduction and improvement of image quality in digital chest radiography by new spatial noise reduction algorithm

Purpose

To evaluate the image quality of low-dose chest digital radiographic images obtained with a new spatial noise reduction algorithm, compared to a conventional de-noising technique.

Materials and methods

In 69 patients, the dose reduction protocol was divided into A, B, and C test groups– 60% (n = 22), 50% (n = 23), and 40% (n = 24) of the baseline dose. In each patient, baseline dose radiographs were obtained with conventional image processing while low-dose images were acquired with new image processing. A set of baseline and low-dose radiographic images per patient was evaluated and scored on a 5-point scale over seven anatomical landmarks (radiolucency of unobscured lung, pulmonary vascularity, trachea, edge of rib, heart border, intervertebral disc space, and pulmonary vessels in the retrocardiac area) and three representative abnormal findings (nodule, consolidation, and interstitial marking) by two thoracic radiologists. A comparison of paired baseline and low-dose images was statistically analyzed using a non-inferiority test based on the paired t-test or the Wilcoxon signed-rank test.

Results

In A, B, and C test groups, the mean dose reduction rate of the baseline radiation dose was 63.4%, 53.9%, and 47.8%, respectively. In all test groups, the upper limit of the 95% confidence interval was less than the non-inferiority margin of 0.5 every seven anatomical landmarks and three representative abnormal findings, which suggested that the image quality of the low-dose image was not inferior to that of the baseline dose image even if the maximum average dose reduction rate was reduced to 47.8% of the baseline dose.

Conclusion

In our study, an image processing technique integrating a new noise reduction algorithm achieved dose reductions of approximately half without compromising image quality for abnormal lung findings and anatomical landmarks seen on chest radiographs. This feature-preserving, noise reduction algorithm adopted in the proposed engine enables a lower radiation dose boundary for the sake of patient’s and radiography technologist’s radiation safety in routine clinical practice, in compliance with regulatory guidelines.

Abdominal Digital Radiography with a Novel Post-Processing Technique: Phantom and Patient Studies

Purpose

Materials and Methods

Results

Conclusion

Robust Quantitative Assessment of Trabecular Microarchitecture in Extremity Cone-Beam CT Using Optimized Segmentation Algorithms

Purpose

In-vivo evaluation of bone microarchitecture remains challenging because of limited resolution of conventional orthopaedic imaging modalities. We investigate the performance of flat-panel detector extremity Cone-Beam CT (CBCT) in quantitative analysis of trabecular bone. To enable accurate morphometry of fine trabecular bone architecture, advanced CBCT pre-processing and segmentation algorithms are developed.

Methods

The study involved 35 transilliac bone biopsy samples imaged on extremity CBCT (voxel size 75 μm, imaging dose ~13 mGy) and gold standard μCT (voxel size 7.67 μm). CBCT image segmentation was performed using (i) global Otsu's thresholding, (ii) Bernsen's local thresholding, (iii) Bernsen's local thresholding with additional histogram-based global pre-thresholding, and (iv) the same as (iii) but combined with contrast enhancement using a Laplacian Pyramid. Correlations between extremity CBCT with the different segmentation algorithms and gold standard μCT were investigated for measurements of Bone Volume over Total Volume (BV/TV), Trabecular Thickness (Tb.Th), Trabecular Spacing (Tb.Sp), and Trabecular Number (Tb.N).

Results

The combination of local thresholding with global pre-thresholding and Laplacian contrast enhancement outperformed other CBCT segmentation methods. Using this optimal segmentation scheme, strong correlation between extremity CBCT and μCT was achieved, with Pearson coefficients of 0.93 for BV/TV, 0.89 for Tb.Th, 0.91 for Tb.Sp, and 0.88 for Tb.N (all results statistically significant). Compared to a simple global CBCT segmentation using Otsu's algorithm, the advanced segmentation method achieved ~20% improvement in the correlation coefficient for Tb.Th and ~50% improvement for Tb.Sp.

Conclusions

Extremity CBCT combined with advanced image pre-processing and segmentation achieves high correlation with gold standard μCT in measurements of trabecular microstructure. This motivates ongoing development of clinical applications of extremity CBCT in in-vivo evaluation of bone health e.g. in early osteoarthritis and osteoporosis.

Evaluation of a Mathematical Model for Digital Image Enhancement

Objective : The purpose of this study is to compare the detected number of holes on a stepwedge on images resulting from the application of the 5th degree polynomial model compared to the images resulting from the application of linear enhancement. Material and Methods : A 10-step aluminum step wedge with holes randomly drilled on each step was exposed with three different kVp and five exposure times per kVp on a Schick33^® sensor. The images were enhanced by brightness/contrast adjustment, histogram equalization and with the 5th degree polynomial model and compared to the original non-enhanced images by six observers in two separate readings. Results : There was no significant difference between the readers and between the first and second reading. There was a significant three-factor interaction among Method, Exposure time, and kVp in detecting holes. The overall pattern was: “Poly” results in the highest counts, “Original” in the lowest counts, with “B/C” and “Equalized” intermediate. Conclusion : The 5th degree polynomial model showed more holes when compared to the other modalities.

Localized Energy-Based Normalization of Medical Images: Application to Chest Radiography

Automated quantitative analysis systems for medical images often lack the capability to successfully process images from multiple sources. Normalization of such images prior to further analysis is a possible solution to this limitation. This work presents a general method to normalize medical images and thoroughly investigates its effectiveness for chest radiography (CXR). The method starts with an energy decomposition of the image in different bands. Next, each band's localized energy is scaled to a reference value and the image is reconstructed. We investigate iterative and local application of this technique. The normalization is applied iteratively to the lung fields on six datasets from different sources, each comprising 50 normal CXRs and 50 abnormal CXRs. The method is evaluated in three supervised computer-aided detection tasks related to CXR analysis and compared to two reference normalization methods. In the first task, automatic lung segmentation, the average Jaccard overlap significantly increased from 0.72±0.30 and 0.87±0.11 for both reference methods to with normalization. The second experiment was aimed at segmentation of the clavicles. The reference methods had an average Jaccard index of 0.57±0.26 and 0.53±0.26; with normalization this significantly increased to . The third experiment was detection of tuberculosis related abnormalities in the lung fields. The average area under the Receiver Operating Curve increased significantly from 0.72±0.14 and 0.79±0.06 using the reference methods to with normalization. We conclude that the normalization can be successfully applied in chest radiography and makes supervised systems more generally applicable to data from different sources.

Normalizing computed tomography data reconstructed with different filter kernels: effect on emphysema quantification

Objectives

To propose and evaluate a method to reduce variability in emphysema quantification among different computed tomography (CT) reconstructions by normalizing CT data reconstructed with varying kernels.

Methods

We included 369 subjects from the COPDGene study. For each subject, spirometry and a chest CT reconstructed with two kernels were obtained using two different scanners. Normalization was performed by frequency band decomposition with hierarchical unsharp masking to standardize the energy in each band to a reference value. Emphysema scores (ES), the percentage of lung voxels below -950 HU, were computed before and after normalization. Bland-Altman analysis and correlation between ES and spirometry before and after normalization were compared. Two mixed cohorts, containing data from all scanners and kernels, were created to simulate heterogeneous acquisition parameters.

Results

The average difference in ES between kernels decreased for the scans obtained with both scanners after normalization (7.7 ± 2.7 to 0.3 ± 0.7; 7.2 ± 3.8 to -0.1 ± 0.5). Correlation coefficients between ES and FEV₁, and FEV₁/FVC increased significantly for the mixed cohorts.

Conclusions

Normalization of chest CT data reduces variation in emphysema quantification due to reconstruction filters and improves correlation between ES and spirometry.

Key Points

• Emphysema quantification is sensitive to the reconstruction kernel used.

• Normalization allows comparison of emphysema quantification from images reconstructed with varying kernels.

• Normalization allows comparison of emphysema quantification obtained with scanners from different manufacturers.

• Normalization improves correlation of emphysema quantification with spirometry.

• Normalization can be used to compare data from different studies and centers.

[Detection of lung nodules. New opportunities in chest radiography]

BACKGROUND

Chest radiography still represents the most commonly performed X-ray examination because it is readily available, requires low radiation doses and is relatively inexpensive. However, as previously published, many initially undetected lung nodules are retrospectively visible in chest radiographs.

STANDARD RADIOLOGICAL METHODS

The great improvements in detector technology with the increasing dose efficiency and improved contrast resolution provide a better image quality and reduced dose needs.

METHODICAL INNOVATIONS

The dual energy acquisition technique and advanced image processing methods (e.g. digital bone subtraction and temporal subtraction) reduce the anatomical background noise by reduction of overlapping structures in chest radiography. Computer-aided detection (CAD) schemes increase the awareness of radiologists for suspicious areas.

RESULTS

The advanced image processing methods show clear improvements for the detection of pulmonary lung nodules in chest radiography and strengthen the role of this method in comparison to 3D acquisition techniques, such as computed tomography (CT).

ASSESSMENT

Many of these methods will probably be integrated into standard clinical treatment in the near future. Digital software solutions offer advantages as they can be easily incorporated into radiology departments and are often more affordable as compared to hardware solutions.

A study on mastectomy samples to evaluate breast imaging quality and potential clinical relevance of differential phase contrast mammography

OBJECTIVES

Differential phase contrast and scattering-based x-ray mammography has the potential to provide additional and complementary clinically relevant information compared with absorption-based mammography. The purpose of our study was to provide a first statistical evaluation of the imaging capabilities of the new technique compared with digital absorption mammography.

MATERIALS AND METHODS

We investigated non-fixed mastectomy samples of 33 patients with invasive breast cancer, using grating-based differential phase contrast mammography (mammoDPC) with a conventional, low-brilliance x-ray tube. We simultaneously recorded absorption, differential phase contrast, and small-angle scattering signals that were combined into novel high-frequency-enhanced images with a dedicated image fusion algorithm. Six international, expert breast radiologists evaluated clinical digital and experimental mammograms in a 2-part blinded, prospective independent reader study. The results were statistically analyzed in terms of image quality and clinical relevance.

RESULTS

The results of the comparison of mammoDPC with clinical digital mammography revealed the general quality of the images to be significantly superior (P < 0.001); sharpness, lesion delineation, as well as the general visibility of calcifications to be significantly more assessable (P < 0.001); and delineation of anatomic components of the specimens (surface structures) to be significantly sharper (P < 0.001). Spiculations were significantly better identified, and the overall clinically relevant information provided by mammoDPC was judged to be superior (P < 0.001).

CONCLUSIONS

Our results demonstrate that complementary information provided by phase and scattering enhanced mammograms obtained with the mammoDPC approach deliver images of generally superior quality. This technique has the potential to improve radiological breast diagnostics.

Study on construction of a medical x-ray direct digital radiography system and hybrid preprocessing methods

We construct a medical X-ray direct digital radiography (DDR) system based on a CCD (charge-coupled devices) camera. For the original images captured from X-ray exposure, computer first executes image flat-field correction and image gamma correction, and then carries out image contrast enhancement. A hybrid image contrast enhancement algorithm which is based on sharp frequency localization-contourlet transform (SFL-CT) and contrast limited adaptive histogram equalization (CLAHE), is proposed and verified by the clinical DDR images. Experimental results show that, for the medical X-ray DDR images, the proposed comprehensive preprocessing algorithm can not only greatly enhance the contrast and detail information, but also improve the resolution capability of DDR system.

Feature and contrast enhancement of mammographic image based on multiscale analysis and morphology

A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach bases on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid operator is applied to transform the mammography into different scale subband images. In addition, the detail or high frequency subimages are equalized by contrast limited adaptive histogram equalization (CLAHE) and low-pass subimages are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by contrast limited adaptive histogram equalization and mathematical morphology, respectively. The enhanced image is processed by global nonlinear operator. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is measured by contrast evaluation criterion for image, signal-noise-ratio (SNR), and contrast improvement index (CII).

Quantitative measurement method for possible rib fractures in chest radiographs

Objectives

This paper proposes a measurement method to quantify the abnormal characteristics of the broken parts of ribs using local texture and shape features in chest radiographs.

Methods

Our measurement method comprises two steps: a measurement area assignment and sampling step using a spline curve and sampling lines orthogonal to the spline curve, and a fracture-ness measurement step with three measures, asymmetry and gray-level co-occurrence matrix based measures (contrast and homogeneity). They were designed to quantify the regional shape and texture features of ribs along the centerline. The discriminating ability of our method was evaluated through region of interest (ROI) analysis and rib fracture classification test using support vector machine.

Results

The statistically significant difference was found between the measured values from fracture and normal ROIs; asymmetry (p < 0.0001), contrast (p < 0.001), and homogeneity (p = 0.022). The rib fracture classifier, trained with the measured values in ROI analysis, detected every rib fracture from chest radiographs used for ROI analysis, but it also classified some unbroken parts of ribs as abnormal parts (8 to 17 line sets; length of each line set, 2.998 ± 2.652 mm; length of centerlines, 131.067 ± 29.460 mm).

Conclusions

Our measurement method, which includes a flexible measurement technique for the curved shape of ribs and the proposed shape and texture measures, could discriminate the suspicious regions of ribs for possible rib fractures in chest radiographs.

Non-linear direct multi-scale image enhancement based on the luminance and contrast masking characteristics of the human visual system

Image enhancement is a crucial pre-processing step for various image processing applications and vision systems. Many enhancement algorithms have been proposed based on different sets of criteria. However, a direct multi-scale image enhancement algorithm capable of independently and/or simultaneously providing adequate contrast enhancement, tonal rendition, dynamic range compression, and accurate edge preservation in a controlled manner has yet to be produced. In this paper, a multi-scale image enhancement algorithm based on a new parametric contrast measure is presented. The parametric contrast measure incorporates not only the luminance masking characteristic, but also the contrast masking characteristic of the human visual system. The formulation of the contrast measure can be adapted for any multi-resolution decomposition scheme in order to yield new human visual system-inspired multi-scale transforms. In this article, it is exemplified using the Laplacian pyramid, discrete wavelet transform, stationary wavelet transform, and dual-tree complex wavelet transform. Consequently, the proposed enhancement procedure is developed. The advantages of the proposed method include: 1) the integration of both the luminance and contrast masking phenomena; 2) the extension of non-linear mapping schemes to human visual system inspired multi-scale contrast coefficients; 3) the extension of human visual system-based image enhancement approaches to the stationary and dual-tree complex wavelet transforms, and a direct means of; 4) adjusting overall brightness; and 5) achieving dynamic range compression for image enhancement within a direct multi-scale enhancement framework. Experimental results demonstrate the ability of the proposed algorithm to achieve simultaneous local and global enhancements.

A mathematical model relating changes of grey values to changes of thicknesses of a stepwedge

The purpose of this report is to present a mathematical model relating changes in grey values to changes of thicknesses of a stepwedge. Radiographs of a stepwedge were obtained through a limited exposure range on a single Kodak 6100 charge-coupled device detector at 63 kVp and 70 kVp. Grey values from each step were evaluated relative to the corresponding step thickness. All possible regression fits were evaluated based on their coefficient of determination (R(2)) value and their mean squared errors (MSEs) relative to the original thickness. For all exposure settings, the fifth-degree polynomial was the best possible fit, with the highest R(2) value and the lowest MSE.

Development of digital reconstructed radiography software at new treatment facility for carbon-ion beam scanning of National Institute of Radiological Sciences

To increase the accuracy of carbon ion beam scanning therapy, we have developed a graphical user interface-based digitally-reconstructed radiograph (DRR) software system for use in routine clinical practice at our center. The DRR software is used in particular scenarios in the new treatment facility to achieve the same level of geometrical accuracy at the treatment as at the imaging session. DRR calculation is implemented simply as the summation of CT image voxel values along the X-ray projection ray. Since we implemented graphics processing unit-based computation, the DRR images are calculated with a speed sufficient for the particular clinical practice requirements. Since high spatial resolution flat panel detector (FPD) images should be registered to the reference DRR images in patient setup process in any scenarios, the DRR images also needs higher spatial resolution close to that of FPD images. To overcome the limitation of the CT spatial resolution imposed by the CT voxel size, we applied image processing to improve the calculated DRR spatial resolution. The DRR software introduced here enabled patient positioning with sufficient accuracy for the implementation of carbon-ion beam scanning therapy at our center.

The first analysis and clinical evaluation of native breast tissue using differential phase-contrast mammography

OBJECTIVES

Phase-contrast and scattering-based x-ray imaging are known to provide additional and complementary information to conventional, absorption-based methods, and therefore have the potential to play a crucial role in medical diagnostics. We report on the first mammographic investigation of 5 native, that is, freshly dissected, breasts carried out with a grating interferometer and a conventional x-ray tube source. Four patients in this study had histopathologically proven invasive breast cancer. One male patient, without the presence of any malignant formations within the resected breast, was included as a control specimen.

MATERIALS AND METHODS

We used a Talbot-Lau grating setup installed on a conventional, low-brilliance x-ray source; the interferometer operated at the fifth Talbot distance, at a tube voltage of 40 kVp with mean energy of 28 keV, and at a current of 25 mA. The device simultaneously recorded absorption, differential phase and small-angle scattering signals from the native breast tissue. These quantities were then combined into novel color- and high-frequency-enhanced radiographic images. Presurgical images (conventional mammography, ultrasonography, and magnetic resonance imaging) supported the findings and clinical relevance was verified.

RESULTS

Our approach yields complementary and otherwise inaccessible information on the electron density distribution and the small-angle scattering power of the sample at the microscopic scale. This information can be used to potentially answer clinically relevant, yet unresolved questions such as unequivocally discerning between malignant and premalignant changes and postoperative scars and distinguishing cancer-invaded regions within healthy tissue.

CONCLUSIONS

We present the first ex vivo images of fresh, native breast tissue obtained from mastectomy specimens using grating interferometry. This technique yields improved diagnostic capabilities when compared with conventional mammography, especially when discerning the type of malignant conversions and their breadth within normal breast tissue. These promising results advance us toward the ultimate goal, using grating interferometry in vivo on humans in a clinical setting.

Ability of chest X-ray to detect faint shadows documented as ground-glass attenuation in images of computed tomography: a comparison between flat-panel detector radiography and film-screen radiography

PURPOSE

To compare flat-panel detector (FPD) radiography and film-screen (FS) radiography in detectability of faint shadows documented as ground-glass attenuation (GGA) areas in images of computed tomography (CT).

MATERIALS AND METHODS

Study population was comprised of 50 patients who underwent FS and another 50 patients who underwent FPD. Standard of reference (SOR) was determined on the basis of area of GGA in all cross-sections of CT, in terms of GGA extent and presence or absence of GGA in each trisected lung fields (GGA distribution). Eight radiologists assessed the GGA extent with the 5-grade scale and the GGA distribution. Inter-observer variances of the GGA extents and distributions, degree of divergences and correspondence in the GGA extent and distributions with SOR, were compared between the FS and FPD by the jackknife method and Fisher's exact test.

RESULTS

Inter-observer variance in the GGA extent and distribution were slightly larger in the FS than in the FPD. The GGA extent scale corresponded with SOR in the FS statistically significantly better (p=0.001), as the correct ratio was 0.428 in the FS and 0.310 in the FPD. Divergence in the GGA extent scale with SOR was smaller in the FS, as average kappa pseudo-value of Kendall's rank correlation coefficient was 0.474 in the FS and 0.433 in the FPD.

CONCLUSION

These results indicate that some lesions of GGA documented in CT may not be reflected and are difficult to be detected in chest X-ray radiographs with the FPD.

Digital image enhancement improves diagnosis of nondisplaced proximal femur fractures

Today most emergency room radiographs are computerized, making digital image enhancement a natural advancement to improve fracture diagnosis. We compared the diagnosis of nondisplaced proximal femur fractures using four different image enhancement methods using standard DICOM (Digital Imaging and Communications in Medicine) after window-leveling optimization. Twenty-nine orthopaedic residents and specialists reviewed 28 pelvic images consisting of 25 occult proximal femur fractures and three images with no fracture, using four different image filters and the original DICOM image. For intertrochanteric fractures, the Retinex filter outperforms the other filters and the original image with a correct fracture type diagnosis rate of 50.6%. The Retinex filter also performs well for diagnosis of other fracture types. The Retinex filter had an interobserver agreement index of 53.5%, higher than the other filters. Sensitivity of fracture diagnosis increased to 85.2% when the Retinex filter was combined with the standard DICOM image. Correct fracture type diagnosis per minute for the Retinex filter was 1.43, outperforming the other filters. The Retinex filter may become a valuable tool in clinical settings for diagnosing fractures.

LEVEL OF EVIDENCE

Level I, diagnostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Digital chest radiography: an update on modern technology, dose containment and control of image quality

The introduction of digital radiography not only has revolutionized communication between radiologists and clinicians, but also has improved image quality and allowed for further reduction of patient exposure. However, digital radiography also poses risks, such as unnoticed increases in patient dose and suboptimum image processing that may lead to suppression of diagnostic information. Advanced processing techniques, such as temporal subtraction, dual-energy subtraction and computer-aided detection (CAD) will play an increasing role in the future and are all targeted to decrease the influence of distracting anatomic background structures and to ease the detection of focal and subtle lesions. This review summarizes the most recent technical developments with regard to new detector techniques, options for dose reduction and optimized image processing. It explains the meaning of the exposure indicator or the dose reference level as tools for the radiologist to control the dose. It also provides an overview over the multitude of studies conducted in recent years to evaluate the options of these new developments to realize the principle of ALARA. The focus of the review is hereby on adult applications, the relationship between dose and image quality and the differences between the various detector systems.

Effect of multiscale processing in digital chest radiography on automated detection of lung nodule with a computer assistance system

The aim of this study is to evaluate the effect of multiscale processing in digital chest radiography on automated detection of lung nodule with a computer-aided diagnosis (CAD) system. The study involved 58 small-nodule patient cases and 58 normal cases. The 58 patient cases included a total of 64 noncalcified lung nodules up to 15 mm in diameter. Each case underwent an examination with a digital radiography system (Digital Diagnost, Philips Medical Systems), and the acquired image was processed by the following three types of multiscale processing (Unique Image Processing Package, Philips Medical Systems) respectively: (1) standard image from the default processing parameter (structure preference, 0.0), (2) high-pass image with structure preference of 0.4, (3) low-pass image with structure preference of -0.4. The CAD output images were produced with a real-time computer assistance system (IQQAtrade mark-Chest, EDDA Technology). Two experienced chest radiologists established the nodule gold standard by consensus reading according to computed tomography results, and analyzed and recorded the detection of lung nodules and false-positive detections of these CAD output images. For the entire cases involved (each case with three types of different processing), a total of 348 observations were evaluated by the receiver operating characteristic (ROC) analysis. The mean area under the ROC curve (A ( z )) value was 0.700 for the standard images, 0.587 for the high-pass images, and 0.783 for the low-pass images. There were statistically significant A (z) values among these three types of processed images (p < 0.01). Multiscale processing in digital chest radiography can affect the automated detection of lung nodule by CAD, which is consistent with effects from visual inspection.

Does image quality matter? Impact of resolution and noise on mammographic task performance

The purpose of this study was to examine the effects of different resolution and noise levels on task performance in digital mammography. This study created an image set with images at three different resolution levels, corresponding to three digital display devices, and three different noise levels, with noise magnitudes similar to full clinical dose, half clinical dose, and quarter clinical dose. The images were read by five experienced breast imaging radiologists. The data were then analyzed to compute two accuracy statistics (overall classification accuracy and lesion detection accuracy) and performance at four diagnostic tasks (detection of microcalcifications, benign masses, malignant masses, and discrimination of benign and malignant masses). Human observer results showed decreasing display resolution had little effect on overall classification accuracy and individual diagnostic task performance, but increasing noise caused overall classification accuracy to decrease by a statistically significant 21% as the breast dose went to one quarter of its normal clinical value. The noise effects were most prominent for the tasks of microcalcification detection and mass discrimination. When the noise changed from full clinical dose to quarter clinical dose, the microcalcification detection performance fell from 89% to 67% and the mass discrimination performance decreased from 93% to 79%, while malignant mass detection performance remained relatively constant with values of 88% and 84%, respectively. As a secondary aim, the image set was also analyzed by two observer models to examine whether their performance was similar to humans. Observer models differed from human observers and each other in their sensitivity to resolution degradation and noise. The primary conclusions of this study suggest that quantum noise appears to be the dominant image quality factor in digital mammography, affecting radiologist performance much more profoundly than display resolution.

Improving mammographic decision accuracy by incorporating observer ratings with interpretation time

Mammography is currently the most established technique for the early detection of breast cancer. However, mammography would benefit from further improvements as it does produce some errors, such as not finding all early-stage cancers. The objectives of this study were first, to measure the timing of correct and incorrect reading decisions in mammography and second, to exploit those dependencies to improve accuracy in mammographic interpretation. To address these objectives, an experiment was conducted where experienced breast imaging radiologists reviewed 400 mammographic regions equally divided among images that contained simulated benign masses, malignant masses, malignant microcalcifications and no lesions. The experiment recorded the radiologists' decision as well as the length of time the mammogram was interpreted in. The experiment results showed that incorrect detection as well as incorrect classification decisions were associated with longer interpretation times (p<0.0001). The timing results were used to create a model that would flag cases for review that had a higher probability of error. The flagged cases had a median accuracy drop of 13% for detection decisions and 16% for classification decisions compared with unflagged cases. This suggests that interpretation time can be incorporated into mammographic decision-making in order to identify cases with higher probabilities of perceptual error that require further review.

Digital mammography: effects of reduced radiation dose on diagnostic performance

PURPOSE

To experimentally determine the relationship between radiation dose and observer accuracy in the detection and discrimination of simulated lesions for digital mammography.

MATERIALS AND METHODS

This HIPAA-compliant study received institutional review board approval; the informed consent requirement was waived. Three hundred normal craniocaudal images were selected from an existing database of digital mammograms. Simulated mammographic lesions that mimicked benign and malignant masses and clusters of microcalcifications (3.3-7.4 cm in diameter) were then superimposed on images. Images were rendered without and with added radiographic noise to simulate effects of reducing the radiation dose to one half and one quarter of the clinical dose. Images were read by five experienced breast imaging radiologists. Results were analyzed to determine effects of reduced dose on overall interpretation accuracy, detection of microcalcifications and masses, discrimination between benign and malignant masses, and interpretation time.

RESULTS

Overall accuracy decreased from 0.83 with full dose to 0.78 and 0.62 with half and quarter doses, respectively. The decrease associated with transition from full dose to quarter dose was significant (P < .01), primarily because of an effect on detection of microcalcifications (P < .01) and discrimination of masses (P < .05). The level of dose reduction did not significantly affect detection of malignant masses (P > .5). However, reduced dose resulted in an increased mean interpretation time per image by 28% (P < .0001).

CONCLUSION

These findings suggest that dose reduction in digital mammography has a measurable but modest effect on diagnostic accuracy. The small magnitude of the effect in response to the drastic reduction of dose suggests potential for modest dose reductions in digital mammography.

Comparison of LCD and CRT displays based on efficacy for digital mammography

RATIONALE AND OBJECTIVES

To compare two display technologies, cathode ray tube (CRT) and liquid crystal display (LCD), in terms of diagnostic accuracy for several common clinical tasks in digital mammography.

MATERIALS AND METHODS

Simulated masses and microcalcifications were inserted into normal digital mammograms to produce an image set of 400 images. Images were viewed on one CRT and one LCD medical-quality display device by five experienced breast-imaging radiologists who rated the images using a categorical rating paradigm. The observer data were analyzed to determine overall classification accuracy, overall lesion detection accuracy, and accuracy for four specific diagnostic tasks: detection of benign masses, malignant masses, and microcalcifications, and discrimination of benign and malignant masses.

RESULTS

Radiologists had similar overall classification accuracy (LCD: 0.83 +/- 0.01, CRT: 0.82 +/- 0.01) and lesion detection accuracy (LCD: 0.87 +/- 0.01, CRT: 0.85 +/- 0.01) on both displays. The difference in accuracy between LCD and CRT for the detection of benign masses, malignant masses, and microcalcifications, and discrimination of benign and malignant masses was -0.019 +/- 0.009, 0.020 +/- 0.008, 0.012 +/- 0.013, and 0.0094 +/- 0.011, respectively. Overall, the two displays did not exhibit any statistically significant difference (P > .05).

CONCLUSION

This study explored the suitability of two different soft-copy displays for the viewing of mammographic images. It found that LCD and CRT displays offer similar clinical utility for mammographic tasks.

Fast adaptive unsharp masking with programmable mediaprocessors

Unsharp masking is a widely used image-enhancement method in medical imaging. Hardware-based solutions can be developed to support high computational demand for unsharp masking, but they suffer from limited flexibility. Software solutions can easily incorporate new features and modify key parameters, such as filtering kernel size, but they have not been able to meet the fast computing requirement. Modern programmable mediaprocessors can meet both fast computing and flexibility requirements, which will benefit medical image computing. In this article, we present fast adaptive unsharp masking on two leading mediaprocessors or high-end digital signal processors, Hitachi/Equator Technologies MAP-CA and Texas Instruments TMS320C64x. For a 2k x 2k 16-bit image, our adaptive unsharp masking with a 201 x 201 boxcar kernel takes 225 ms on a 300-MHz MAP-CA and 74 ms on a 600-MHz TMS320C64x. This fast unsharp masking enables technologists and/or physicians to adjust parameters interactively for optimal quality assurance and image viewing.

Principles of image processing in digital chest radiography

Image processing has a major impact on image quality and diagnostic performance of digital chest radiographs. Goals of processing are to reduce the dynamic range of the image data to capture the full range of attenuation differences between lungs and mediastinum, to improve the modulation transfer function to optimize spatial resolution, to enhance structural contrast, and to suppress image noise. Image processing comprises look-up table operations and spatial filtering. Look-up table operations allow for automated signal normalization and arbitrary choice of image gradation. The most simple and still widely applied spatial filtering algorithms are based on unsharp masking. Various modifications were introduced for dynamic range reduction and MTF restoration. More elaborate and more effective are multi-scale frequency processing algorithms. They are based on the subdivision of an image in multiple frequency bands according to its structural composition. This allows for a wide range of image manipulations including a size-independent enhancement of low-contrast structures. Principles of the various algorithms will be explained and their impact on image appearance will be illustrated by clinical examples. Optimum and sub-optimum parameter settings are discussed and pitfalls will be explained.

Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy

Spatial unsharp-mask processing and its variants are commonly used in x-ray radiography to enhance image contrast. We investigated the effect of three unsharp-masking filter kernels of different sizes on the detection of an advanced guidewire tip in simulated x-ray fluoroscopy image sequences. To isolate the effect of visual temporal processing, we repeated the experiments on single images. Filter gains were selected so that all three kernels increased the contrast of a 0.018-in. (0.457-mm) guidewire by a factor of 2 but had different effects on image noise and signal profiles. There was no statistically significant effect of unsharp masking on human-observer performance in single images. However, all three kernels significantly improved average performance in image sequences, and the guidewire contrast required for detection was reduced by 32%-40%. A prewhitening channelized observer model predicted the disparity between sequences and single images and fitted measurements at different kernel sizes well. A nonprewhitening observer model did not. We conclude that unsharp masking is a simple and effective method of improving guidewire visualization in fluoroscopically guided interventional procedures and that quantitative image quality studies are essential for evaluation of image-processing techniques in sequences such as x-ray fluoroscopy.

Multiscale contrast enhancement for radiographies: Laplacian Pyramid versus fast wavelet transform

Contrast enhancement of radiographies based on a multiscale decomposition of the images recently has proven to be a far more versatile and efficient method than regular unsharp-masking techniques, while containing these as a subset. In this paper, we compare the performance of two multiscale-methods, namely the Laplacian Pyramid and the fast wavelet transform (FWT). We find that enhancement based on the FWT suffers from one serious drawback-the introduction of visible artifacts when large structures are enhanced strongly. By contrast, the Laplacian Pyramid allows a smooth enhancement of large structures, such that visible artifacts can be avoided. Only for the enhancement of very small details, for denoising applications or compression of images, the FWT may have some advantages over the Laplacian Pyramid.

Comparison of tomosynthesis methods used with digital mammography

RATIONALE AND OBJECTIVES

The authors performed this study to investigate the potential applicability of tomosynthesis to digital mammography. Four methods of tomosynthesis-tuned aperture computed tomography (TACT)-backprojection, TACT-iterative restoration, iterative reconstruction with expectation maximization, and Bayesian smoothing-were compared to planar mammography and analyzed in terms of their contrast-detail characteristics. Specific comparisons between the tomosynthesis methods were not attempted in this study.

MATERIALS AND METHODS

A full-field, amorphous, silicon-based, flat-panel digital mammographic system was used to obtain planar and tomosynthesis projection images. A composite tomosynthesis phantom with a centrally located contrast-detail insert was used as the object of interest. The total exposure for multiple views with tomosynthesis was always equal to or less than that for the planar technique. Algorithms were used to reconstruct the object from the acquired projections.

RESULTS

Threshold contrast characteristics with all tomosynthesis reconstruction methods were significantly better than those with planar mammography, even when planar mammography was performed at more than twice the exposure level. Reduction of out-of-plane structural components was observed in all the tomosynthesis methods analyzed.

CONCLUSION

The contrast-detail trends of all the tomosynthesis methods analyzed in this study were better than those of planar mammography. Further optimization of the algorithms could lead to better image reconstruction, which would improve visualization of valuable diagnostic information.