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Results for “Radiographic Image Enhancement”

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At least 19 recordsLinked to original sources
PubMed2006

Preliminary study on diffraction enhanced radiographic imaging for a canine model of cartilage damage.

OBJECTIVE: To demonstrate the ability of a novel radiographic technique, Diffraction Enhanced Radiographic Imaging (DEI), to render high contrast images of canine knee joints for identification of cartilage lesions in situ. METHODS: DEI was carried out at the X-15A beamline at Brookhaven National Laboratory on intact canine knee joints with varying levels of cartilage damage. Two independent observers graded the DE images for lesions and these grades were correlated to the gross morphological grade. RESULTS: The correlation of gross visual grades with DEI grades for the 18 canine knee joints as determined by observer 1 (r2 = 0.8856, P = 0.001) and observer 2 (r2 = 0.8818, P = 0.001) was high. The overall weighted kappa value for inter-observer agreement was 0.93, thus considered high agreement. CONCLUSION: The present study is the first study for the efficacy of DEI for cartilage lesions in an animal joint, from very early signs through erosion down to subchondral bone, representing the spectrum of cartilage changes occurring in human osteoarthritis (OA). Here we show that DEI allows the visualization of cartilage lesions in intact canine knee joints with good accuracy. Hence, DEI may be applicable for following joint degeneration in animal models of OA.

Animals↗
PubMedDate not supplied

Refraction effects of diffraction-enhanced radiographic imaging: a new look at bone.

The objective of this study was to demonstrate the ability of a novel radiographic technology-diffraction-enhanced imaging-to detect contrast in bone tissue through absorption, refraction, and scatter rejection. Diffraction-enhanced imaging uses a synchrotron x-ray beam to produce images of high contrast by measuring the object's refraction and ultra-small angle scattering of x-rays in addition to the attenuation measured by conventional radiography. We present evidence that diffraction-enhanced imaging provides contrast enhancement at the edges of cortical and cancellous bone and a three-dimensional appearance of trabeculae.

Animals↗
PubMed2001

Radiographic image enhancement. Part I: spatial domain techniques.

Digital image enhancement techniques provide a multitude of choices for improving the visual quality of diagnostic images. Appropriate choice of such techniques is greatly influenced by the imaging modality, task at hand and viewing conditions. This sequence of two articles will provide an overview of underlying concepts, along with algorithms commonly used for radiographic image enhancement. The first article focuses on spatial domain techniques for radiographic image enhancement, with particular reference to point processing methods, histogram modification and unsharp masking.

Algorithms↗
PubMed1987

Digital image processing of dentomaxillofacial radiographs.

The improvement in the image quality of dentomaxillofacial radiographs (panoramic radiographs) with the use of a digital image-processing system was examined. Linear and nonlinear unsharp masking techniques were employed for image processing. The quality of the processed images was found to be markedly improved over that in original radiographs. The detail visibility of linearly enhanced images, especially in low-density areas, was superior to that of nonlinearly enhanced images, although the presence of more artifacts and more noise was noted in linearly enhanced images. Radiographic diagnosis in the dentomaxillofacial region can be improved with this system.

Humans↗
PubMed1988

[Digital radiographic image enhancement in bone diagnosis--initial clinical results].

34 patients with skeletal alterations mostly in the periphery were investigated by digital image intensifier radiography (DIIR). A high resolution image-intensifier system (1024 x 1024 matrix, 40 cm, 28 cm, 14 cm image intensifier, maximal spatial resolution: 3.6 lp/mm) was available. The image quality was diagnostic sufficient in 76% using DIIR. A good or very good image quality of fine-structures was obtained only in 41%. The quality deficits in comparison to conventional radiograms were particularly obvious in investigation of the phalangeals. Logarithmic amplification and software upgrading lead after these first clinical investigations to a better image quality.

Adult↗
PubMed1989

[The application of fractal technics for the enhancement of radiographic images].

This paper deals with digital radiological image processing, with a special emphasis on quantitative measurement extraction aimed at discriminating different lung pathologies. Texture analysis of these images, not easily performed by the human eye, can be carried out by means of fractal techniques, which allow different textures to be characterized by a single parameter--i.e. the fractal dimension. To extract the fractal dimension of an image, the so-called "blanket" method is employed, which allows the average fractal dimension of an image area to be evaluated. The result of this processing is a new image whose points are assigned the average fractal dimension value of the area they belong to. The behaviors of fractal dimension histograms related to various simulations of lung pathologies are notably different, which allows such pathologies to be effectively characterized and differentiated on a quantitative basis. The radiographic images the "blanket" method was applied to are related to simulations of both pathological and healthy tissues. The behaviors of fractal dimension histograms and the average fractal dimension values allow the characterization of the different pathologies both for single tissues and in case of superimposition of a healthy tissue on a pathological one. The promising simulation results have encouraged us to carry out the present experimental investigation in the field of lung neoplasms.

Humans↗
PubMed1988

Effect of image enhancement for detectability of bone lesions in digitized intraoral radiographs.

Digital image enhancement is concerned with the computer-controlled manipulation of image information. The aim of this study was to evaluate whether diagnostic accuracy would improve in digitally enhanced images of radiographs with impaired density. Each of 83 dry mandibles was divided into four regions. By random assignment it was decided for each region whether or not a hole should be drilled. Three intraoral radiographs (3 x 4 cm) were performed of each region at different exposure times: 2.0 s, 0.60 s, and 0.16 s and interpreted. The radiographs were thereafter recorded by a video camera connected to an IBM-PC. The personal computer held a hardware digitization card defined at a 512 x 512 x 8 matrix resolution on the basis of which a software program with image enhancement facilities was developed. The light and dark radiographs were digitally enhanced by the use of contrast stretching and smoothing filters. The light (0.16 s) original radiographs were less accurate than the ones with optimal density (0.60 s) while no significant differences were found between dark (2.0 s) and optimal density original radiographs. No significant differences were found between original and digitized radiographs of optimal density and digitally enhanced images of light or dark radiographs. The diagnostic accuracy obtained from optimal density radiographs can thus be maintained in digitized dark radiographs and in light radiographs with a four-times dose reduction after digital image enhancement.

Animals↗
PubMed2001

Radiographic digital image enhancement. Part II: transform domain techniques.

Digital image enhancement techniques can have a significant impact on the diagnostic quality of a radiographic image. Selection of an image enhancement technique is a function of image content and its attributes of interest. The diagnostic value of a radiographic image is commonly reduced by its intrinsic limitations as well as interference from unwanted signals. In this second article on radiographic image enhancement the Fourier transform, the most commonly used transformation method, is used to examine examples of methods for image enhancement, with particular emphasis on the removal or reduction of noise.

Artifacts↗
PubMed2006

Resolution enhancement in digital x-ray imaging.

We have developed a restoration method for radiographs that enhances image sharpness and reveals bone microstructures that were initially hidden in the soft-tissue glare. The method is two fold: the image is first deconvolved using the Richardson-Lucy algorithm and is then divided with a signal modelling the soft-tissue distribution to increase the overall contrast. Each step has its own merits but the power of the restoration method lies in their combination. The originality of the method is its reliance on a priori information at each step in the processing. We have measured and modelled analytically the point-spread function of a low-dose gas microstrip x-ray detector at several beam energies. We measured the relationship between the local image intensity and the noise variance for these images. The soft-tissue signal was also modelled using a minimum-curvature filtering technique. These results were then combined into an image deconvolution procedure that uses wavelet filtering to reduce restoration noise while keeping the enhanced small-scale features. The method was applied successfully to images of a human-torso phantom and improved the contrast of small details on the bones and in the soft tissues. We measured a mean 54% increase in signal to noise ratio and a mean 105% increase in contrast to noise ratio in the 70 and 140 kVp images we analysed. The method was designed to facilitate the analysis of radiographs by relying on two levels of visual inspection. The contrast of the full image is first enhanced by division with the signal modelling the soft-tissue distribution. Based on the result, a radiologist might decide to zoom in on a given image section. The full restoration method is then applied to that region of interest. Indeed, full image deconvolution is often unnecessary since enhanced small-scale details are not visible at large scale; only the section of interest is processed which is more efficient.

Algorithms↗
PubMed1999

Lossy compression should not be used in certain imaging applications such as chest radiography. For the proposition.

Computational techniques are frequently used to compress image data so that transmission and storage requirements are reduced. If the computational techniques result in no loss in image resolution, the technique is referred to as lossless compression. Greater compression of data may yield some loss in spatial or temporal resolution, and is referred to as lossy compression. In some radiologic examinations [e.g., gastrointestinal (GI) studies], some resolution loss may be tolerable, whereas in others (chest examinations and mammography) it conceivably could result in missed pathology. Without lossy compression, however, data requirements can be overwhelming for transmission, storage and retrieval of images such as chest films. The unanswered question, addressed in this Point/Counterpoint issue, is whether some degree of lossy compression can be tolerated in chest radiography.

Humans↗
PubMed1988

The enhancement of radiographic images from a multiwire camera using a maximum entropy algorithm.

The multiwire camera (MWC) produces high speed, quantitative autoradiography of radiolabelled substances in two-dimensional systems. While greatly superior to film-based systems in respect of speed and quantitativity the MWC has significantly poorer spatial resolution (particularly for high energy beta-emitting radiolabels) and the performance is ultimately limited by the noise induced in the images by Poisson statistics and counter background. Processing the MWC images with a maximum entropy algorithm significantly improves the performance of the system in these respects. The algorithm has been tested using one-dimensional data taken from images of known tritium, 14C and 125I distributions. Processed images are visually more acceptable with improved quantitative accuracy and spatial resolution. Quantitative accuracy, calculated as the root mean square deviation between an image and the known sample activities, is 10-40% lower for processed images compared with original camera images. Spatial resolution, calculated from slopes in the images representing edges of activity in the sources, is improved by 20-40% for the processed images. The algorithm is used to improve a two-dimensional image from a biological study. The source distribution consisted of a set of circular dots of varying activity. The dots with lowest activity were barely discernible in the raw MWC image but are clearly resolved after processing. The algorithm used is simple and effective and executes acceptably quickly on a personal computer. It should prove useful in any context where the imaging performance of a system is limited by Poisson statistics.

Algorithms↗
PubMedDate not supplied

Image enhancement using computed radiography.

Computed radiography (CR) is emerging as a digital imaging modality for use in conventional radiography. An advantage of CR over film-screen systems is the separation of image acquisition, processing and display. Selection of many different image display characteristics are possible. The system is also able to alter or enhance image details after the radiographic examination has been completed.

Humans↗
PubMed2006

Sliding window adaptive histogram equalization of intraoral radiographs: effect on image quality.

OBJECTIVES: To investigate whether contrast enhancement by non-interactive, sliding window adaptive histogram equalization (SWAHE) can enhance the image quality of intraoral radiographs in the dental clinic. METHODS: Three dentists read 22 periapical and 12 bitewing storage phosphor (SP) radiographs. For the periapical readings they graded the quality of the examination with regard to visually locating the root apex. For the bitewing readings they registered all occurrences of approximal caries on a confidence scale. Each reading was first done on an unprocessed radiograph ("single-view"), and then re-done with the image processed with SWAHE displayed beside the unprocessed version ("twin-view"). The processing parameters for SWAHE were the same for all the images. RESULTS: For the periapical examinations, twin-view was judged to raise the image quality for 52% of those cases where the single-view quality was below the maximum. For the bitewing radiographs, there was a change of caries classification (both positive and negative) with twin-view in 19% of the cases, but with only a 3% net increase in the total number of caries registrations. For both examinations interobserver variance was unaffected. CONCLUSIONS: Non-interactive SWAHE applied to dental SP radiographs produces a supplemental contrast enhanced image which in twin-view reading improves the image quality of periapical examinations. SWAHE also affects caries diagnosis of bitewing images, and further study using a gold standard is warranted.

Algorithms↗
PubMed2005

Visualisation of calcifications and thin collagen strands in human breast tumour specimens by the diffraction-enhanced imaging technique: a comparison with conventional mammography and histology.

Six excised human breast tissue specimens carrying benign and malignant tumours were examined with the diffraction-enhanced imaging technique. Diffraction-enhanced images were compared with diagnostic screen-film mammograms and the correlation with histological information of the specimens was established. The enhanced visibility of calcifications, some of which were smaller than 0.15 mm in diameter, is reported in detail. Fine details of the structures such as strands of collagen and contours between glandular and adipose tissue, which are barely visible at the contrast detection limit in the conventional absorption-based mammograms, are clearly visible in the diffraction-enhanced images. Microscopic study of the stained histopathological sections unequivocally confirms the correlation of the radiographic findings with the morphologic changes in specimens. An increased soft tissue contrast and a combination of information obtained with disparate diffraction-enhanced images provide better visibility of mammographically indistinguishable features. This kind of additional structural information of the breast tissue is required to improve assessment accuracy and earlier detection of the breast lesions. These advances in image quality make the method a very promising candidate for mammography.

Breast Neoplasms↗
PubMed2006

Temporal subtraction in chest radiography: automated assessment of registration accuracy.

Radiologists routinely compare multiple chest radiographs acquired from the same patient over time to more completely understand changes in anatomy and pathology. While such comparisons are achieved conventionally through a side-by-side display of images, image registration techniques have been developed to combine information from two separate radiographic images through construction of a "temporal subtraction image." Although temporal subtraction images provide a powerful mechanism for the enhanced visualization of subtle change, errors in the clinical evaluation of these images may arise from misregistration artifacts that can mimic or obscure pathologic change. We have developed a computerized method for the automated assessment of registration accuracy as demonstrated in temporal subtraction images created from radiographic chest image pairs. The registration accuracy of 150 temporal subtraction images constructed from the computed radiography images of 72 patients was rated manually using a five-point scale ranging from "5-excellent" to "1-poor;" ratings of 3, 4, or 5 reflected clinically acceptable subtraction images, and ratings of 1 or 2 reflected clinically unacceptable images. Gray-level histogram-based features and texture measures are computed at multiple spatial scales within a "lung mask" region that encompasses both lungs in the temporal subtraction images. A subset of these features is merged through a linear discriminant classifier. With a leave-one-out-by-patient training/testing paradigm, the automated method attained an A(z) value of 0.92 in distinguishing between temporal subtraction images that demonstrated clinically acceptable and clinically unacceptable registration accuracy. A second linear discriminant classifier yielded an A(z) value of 0.82 based on a feature subset selected from an independent database of digitized film images. These methods are expected to advance the clinical utility of temporal subtraction images for chest radiography.

Algorithms↗
PubMed2005

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.

Brachytherapy↗
PubMed2006

Evaluation of x-ray diffraction enhanced imaging in the diagnosis of breast cancer.

The significance of the x-ray diffraction enhanced imaging (DEI) technique in the diagnosis of breast cancer and its feasibility in clinical medical imaging are evaluated. Different massive specimens including normal breast tissues, benign breast tumour tissues and malignant breast tumour tissues are imaged with the DEI method. The images are recorded respectively by CCD or x-ray film at different positions of the rocking curve and processed with a pixel-by-pixel algorithm. The characteristics of the DEI images about the normal and diseased tissues are compared. The rocking curves of a double-crystal diffractometer with various tissues are also studied. The differences in DEI images and their rocking curves are evaluated for early diagnosis of breast cancers.

Absorption↗