Showing papers on "Digital mammography published in 1996"

Computer-assisted method and apparatus for analysis of x-ray images using wavelet transforms

Abstract: A computer-assisted diagnostic (CAD) method and apparatus are described for the enhancement and detection of suspicious regions in digital X-ray images, with particular emphasis on early cancer detection using digital mammography. An objective is to improve the sensitivity of detection of suspicious areas such as masses, while maintaining a low false positive detection rate, and to classify masses as benign or malignant. A modular CAD technique has been developed as a potentially automatic and/or second-opinion method for mass detection and classification in digital mammography that may in turn be readily modified for application with different digital X-ray detectors with varying gray-scale and resolution characteristics. The method consists of using a plurality of CAD modules to preprocess and enhance image features in the gray-level, the directional texture, and the morphological domains.

Nature of expertise in searching mammograms for breast masses

Abstract: Eye position of observes representing four levels of training and experience: mammographers; mammography residents; mammographic technologists; and, laypersons were compared to a random search model as they examined a set of nine two-view digital mammogram pairs for breast masses. Analysis of time-to-hit data revealed that mammographers' training and experience combined to produce the most efficient search patterns as measured by the fastest search times to detect breast masses on two views. Scanning patterns of mammography residents and mammographic technologists were less efficient due to wider dispersion of visual attention that was divided between potential breast masses and perturbations in breast parenchyma. Because laypersons lacked training in radiology, bright blobs in the breast image were considered to be intuitively valid target candidates, and these features distracted search by capturing visual attention.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Current status of digital mammography

Abstract: Some inherent limitations to further technical improvement in film-screen mammography exist. Many of these limitations can be overcome effectively with digital mammography, in which image acquisition, display, and storage are performed independently, thus allowing the optimization of each. Presented is a brief background of digital and analog imaging with emphasis on the features and drawbacks of digital mammography systems. Image storage, processing, and display, computer-aided detection and diagnosis, as well as telemammography are also discussed.

Full breast digital mammography device

Abstract: The invention provides a digital x-ray mammography device capable of imaging a full breast. A movable aperture coupled with a movable x-ray image detector permits x-ray image data to be obtained with respect to partially overlapping x-ray beam paths from an x-ray source passing through a human breast. A digital computer programmed with a stitching algorithm produces a composite image of the breast from the image data obtained with respect to each path. In a preferred embodiment, a Schmidt camera images visible light produced at an x-ray to visible light conversion surface onto a digital detector array to produce an overlapping image pane with respect to each overlapping beam path.

Scatter reduction in mammography with air gap.

Abstract: Scatter reduction by air gaps in mammography was investigated. We have experimentally demonstrated that, independently of the imaging geometry, scatter in air‐gap mammography can be well described by a virtual source of scatter (VSS) model. This model postulates that scatter radiation originates from a virtual point source of scatter placed on the central axis between the x‐ray source and the exit surface of a patient at distance δ and utilizes only two parameters: δ and (S/P)0. The (S/P)0 parameter represents scatter‐to‐primary ratio without an air gap and δ is the distance from the exit surface of a patient to the virtual source of scatter. We have experimentally determined the analytical form of the two independent parameters of the VSS model; δ exhibits a linear increase proportional to the radiation field size, does not depend on patient thickness, and is in the 10–30 cm range, while (S/P)0 increases with the field size as a power function and is in the 0.4–1.3 range. In the framework of the VSS model the selectivity, the contrast improvement factor, and the signal‐to‐noise improvement factor were employed to evaluate performance of air‐gap mammography systems. We have demonstrated that selectivity of an air gap rapidly deteriorates at some well‐defined critical value of scatter fraction that has profound consequences on air‐gap performance. Assuming fixed patient exposure, the results shows that, if a contrast limited detection system (such as film/screen mammography) is used, an air gap system can outperform a grid system only if a very large source‐to‐patient (SPD) distance is utilized, which might be possible with new laser‐based x‐ray sources. For the noise limited detection systems (such as digital mammography) even a small SPD (70 cm) and a small air‐gap (20 cm) system will outperform a grid system.

CCD mosaic technique for large-field digital mammography

Abstract: The authors present a novel technique for large-field digital mammography. The instrument uses a mosaic of electronic digital imaging [charge coupled device (CCD)] arrays, novel area scanning, and a radiation exposure and scatter reducing mechanism. The imaging arrays are mounted on a carrier platform in a checker-board pattern mosaic. To fill in the gaps between array-active areas the platform Is repositioned three times and four X-ray exposures are made. The multiple image areas are then recombined by a digital computer to produce a composite image of the entire region. To reduce X-ray scatter and exposure, a lead aperture plate is interposed between X-ray source and patient. The aperture plate has a mosaic of square holes in alignment with the imaging array pattern and the plate is repositioned in synchronism with the carrier platform. The authors discuss proof-of-concept testing demonstrating technical feasibility of their approach. The instrument should be suitable for incorporation into standard mammography units. Unique features of the new technique are: large field coverage (18/spl times/24 cm); high spatial resolution (14-17 lp/mm); scatter rejection; and excellent contrast characteristics and lesion detectability under clinical conditions.

Image compression in digital mammography: Effects on computerized detection of subtle microcalcifications

Abstract: Our previous receiver operating characteristic (ROC) study indicated that the detection accuracy of microcalcifications by radiologists is significantly reduced if mammograms are digitized at 0.1 mm x 0.1 mm. Our recent study also showed that detection accuracy by computer decreases as the pixel size increases from 0.035 mm x 0.035 mm. It is evident that very large matrix sizes have to be used for digitizing mammograms in order to preserve the information in the image. Efficient compression techniques will be needed to facilitate communication and archiving of digital mammograms. In this study, we evaluated two compression techniques: full frame discrete cosine transform (DCT) with entropy coding and Laplacian pyramid hierarchical coding (LPHC). The dependence of their efficiency on the compression parameters was investigated. The techniques were compared in terms of the trade-off between the bit rate and the detection accuracy of subtle microcalcifications by an automated detection algorithm. The mean-square errors in the reconstructed images were determined and the visual quality of the error images was examined. It was found that with the LPHC method, the highest compression ratio achieved without a significant degradation in the detectability was 3.6:1. The full frame DCT method with entropy coding provided a higher compression efficiency of 9.6:1 at comparable detection accuracy. The mean-square errors did not correlate with the detection accuracy of the microcalcifications. This study demonstrated the importance of determining the quality of the decompressed images by the specific requirements of the task for which the decompressed images are to be used. Further investigation is needed for selection of optimal compression technique for digital mammograms.

Detecting abnormalities on mammograms by bilateral comparison

Abstract: An automated system for detecting breast abnormalities should significantly reduce the time needed to examine a mammogram. A system should be able to detect most kinds of abnormalities in order for it to have a positive contribution to a clinical situation. One way of examining mammograms that is used frequently by radiologists is the comparison of left and right breast images. Recent attempts to automate the comparison method have produced very promising results. Two new attempts are presented here. Initially, segmentation of the digitised images involves separating breast tissue from their background. Alignment of the 2 mammograms is then carried out using a single reference-the point of maximum curvature on the breast curve. Finally normalisation is used to minimise differences in illumination between X-ray images before comparison. The first method, single image comparison, involves finding corresponding areas whose intensities differ more than a preset threshold. The results are presented in the form of 2 binary images which are median filtered to eliminate artifacts and to smooth rough borders. The second method, multiple image comparison (MIG), involves generating 8 pairs of images for each original pair of left and right images. MIC uses a combination of processes including adaptive histogram modification, normalisation, grey level thresholding, binary image cleaning and region segmentation. The 8 pairs of images are then bilaterally compared and the resulting images recombined into 1 pair of images. (4 pages)

Digital mammography with a mosaic of CCD arrays

Abstract: A digital mammography device uses a mosaic of electronic digital imaging arrays to scan an x-ray image. The mosaic of arrays is repositioned several times to expose different portions of the image, until the entire image is scanned. The data generated by the arrays during each exposure is stored in a computer. After the final exposure, the computer combines data of the several partial images to produce a composite of the original x-ray image. An aperture plate is used to reduce scatter and the overall exposure of the patient to x-rays.

Storage phosphor-based digital mammography using a low-dose x-ray system optimized for screen-film mammography

Abstract: We are examining the feasibility of performing digital mammography by combining a storage- phosphor image receptor with a highly efficient x-ray system. The image receptor consists of Fuji series HR-V high resolution imaging plates and a Fuji 9000 reader. The x-ray system was developed using multiparameter optimization techniques, with the goal of reducing patient dose as much as possible while retaining acceptable imaging performance. We have measured sensitometric properties, modulation transfer function (MTF), and noise power spectrum (NPS) of the Fuji plates with low-energy x-ray spectra. We have used the measurements, along with information about the x-ray system, to estimate signal-to-noise ratios (SNRs) for objects in a contrast-detail (C-D) phantom. We present the results of our measurements on the Fuji plates, comparisons of calculated and observed C-D diagrams for this system and a conventional system, and comparisons of phantom images and doses for this system to images and doses for a conventional system. We conclude that digital mammography with the system studied is at least feasible since phantom image quality is comparable to that of a conventional system at dose levels that are somewhat lower.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Potential image quality in scintillator-CCD-based x-ray imaging systems for digital radiography and digital mammography

Abstract: The purpose of this work is to investigate the potential image quality of scintillator/CCD-based direct digital medical x-ray imaging systems. The x-ray detector is composed of a scintillating screen to convert x-ray photons into lower energy radiation (UV/visible/NIR) that is then collected by a lens or a fiberoptic taper and converted to an electrical signal by a CCD. The DQE (on-axis geometry) was modeled by extending the analysis used for storage phosphor systems. The effect of various system parameters on the system DQE has been investigated. Two coupling approaches, an array of lenses, and an array of fiberoptic tapers, have been studied. For each coupling approach, two applications, chest radiography and mammography, were examined and the DQE was modeled to be comparable to screen/film systems.

Influence of segmentation on classification of microcalcifications in digital mammography

Abstract: Contrast of microcalcifications can be used to classify benign and malignant types. Different measures for contrast are investigated: mean and maximum contrast, with and without correction for microcalcification size. It is analyzed how the discriminating power of contrast depends on the segmentation process. For classification the k-Nearest-Neighbor method is used and for testing the "leave-one-out-method". Results of an experimental study using a dataset of mammographic images digitized at 2048/spl times/2048 are presented. It is shown that segmentation strongly influences classification.

A multiresolution wavelet analysis and Gaussian Markov random field algorithm for breast cancer screening of digital mammography

Abstract: A novel multiresolution wavelet analysis (MWA) and non-stationary Gaussian Markov random field (GMRF) technique is introduced for the identification of microcalcifications with high accuracy. The hierarchical multiresolution wavelet information in conjunction with the contextual information of the images extracted from GMRF provides a highly efficient technique for microcalcification detection. A Bayesian learning paradigm realized via the expectation maximization (EM) algorithm was also introduced for edge detection or segmentation of larger lesions recorded on the mammograms. The effectiveness of the approach has been extensively tested with a number of mammographic images provided by a local hospital.

Computer Assisted Quality Control and Telemammography.

Abstract: : This purpose of this project, DAMD17-93-J-3015 was to develop systems to enable the integration of mammography into MDIS for digital storage and soft copy display, to allow the acquisition of mammograms in facilities remote from the radiologist who will interpret the images, to develop automated methods of quality control of image quality and to develop methods for the teletransmission of digital mammograms. We have demonstrated the effectiveness of digital mammography using a direct digital method, but in our tests, digitized film was inadequate for diagnosis. We have developed a system for the teletransmission of mammograms that results in hard copy display of adequate diagnostic quality. We have developed a computerized system for the detection of under and over-exposure of mammograms for both digitized screen film mammograms and digitally captured mammograms. We were unable to devise a system for the soft copy display of mammography that provided adequate quality for soft copy interpretation. Implementation with a Fuji FCR 9000 with image processing parameters that we have optimized and printed as hard copy on a 3M 969 laser printer is feasible. Deprad, which is a product of the Analogics Corporation that we helped to design, is a suitable method for teledigital mammography.

Satellite teleradiology test bed for digital mammography

Abstract: Teleradiology offers significant improvement in efficiency and patient compliance over current practices in traditional film/screen-based diagnosis. The increasing number of women who need to be screened for breast cancer, including those in remote rural regions, make the advantages of teleradiology especially attractive for digital mammography. At the same time, the size and resolution of digital mammograms are among the most challenging to support in a cost effective teleradiology system. This paper will describe a teleradiology architecture developed for use with digital mammography by GE Corporate Research and Development in collaboration with Massachusetts General Hospital under National Cancer Institute (NCI/NIH) grant number R01 CA60246-01. The testbed architecture is based on the Digital Imaging and Communications in Medicine (DICOM) standard, created by the American College of Radiology and National Electrical Manufacturers Association. The testbed uses several Sun workstations running SunOS, which emulate a rural examination facility connected to a central diagnostic facility, and uses a TCP-based DICOM application to transfer images over a satellite link. Network performance depends on the product of the bandwidth times the round- trip time. A satellite link has a round trip of 513 milliseconds, making the bandwidth-delay a significant problem. This type of high bandwidth, high delay network is called a Long Fat Network, or LFN. The goal of this project was to quantify the performance of the satellite link, and evaluate the effectiveness of TCP over an LFN. Four workstations have Sun's HSI/S (High Speed Interface) option. Two are connected by a cable, and two are connected through a satellite link. Both interfaces have the same T1 bandwidth (1.544 Megabits per second). The only difference was the round trip time. Even with large window buffers, the time to transfer a file over the satellite link was significantly longer, due to the bandwidth-delay. To compensate for this, TCP extensions for LFNs such as the Window Scaling Option (described in RFC1323) were necessary to optimize the use of the link. A high level analysis of throughput, with and without these TCP extensions, will be discussed. Recommendations will be made as to the critical areas for future work.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Statistical models for the detection of abnormalities in digital mammography

Abstract: This paper introduces statistical methods for the detection of abnormalities in X-ray mammograms. Two types of abnormalities which may be encountered are microcalcification clusters and masses, both of which are possible indicators of breast cancer. Microcalcifications are small deposits of calcium in the breast, which are associated with a high incidence of breast cancer, whilst masses may indicate cancerous growth. While masses are typically of a size which will enable detection under current breast screening procedures, the small size of microcalcifications indicates that a computer assisted analysis is appropriate to enable detection at an early stage. The analysis presented here is evaluated using two sets of data. The first of these is a CIRS phantom image containing clusters of microcalcifications in a range of sizes, and the second is a set of digitized film mammograms depicting both masses and microcalcifications. The authors are indebted to Dr Matthew Freedman of the Georgetown University Medical Centre, Washington D.C. For both of these sets of data. Two approaches have been adopted for the analysis of this data. The first approach is based upon a method that was developed by the authors for the application of detecting objects in sidescan sonar images. Here, the authors add a pre-processing algorithm which suppresses the background variability whilst emphasising the abnormalities. A second method, developed specifically for this application, is based upon a Gibbs random field which is designed to model pixel interactions within the image.

Wavelet methods for combining CAD with enhancement of mammograms

Abstract: Computer-aided diagnosis techniques have been proposed as second opinion providers in digital mammography. This paper considers a new method of presenting CAD output to the radiologist. Instead of superimposing detected pixels or arrows on the mammogram, we adaptively enhance the most suspicious regions according to the weight indicated by the test statistic at the detector output. In so doing, CAD false positives promise to be less obtrusive to the viewer, and lesions missed by CAD (false negatives) may still be detected by the radiologist. In our method the entire mammogram is enhanced to some (spatially varying) degree. Enhancement is realized by applying nonlinear operators to wavelet coefficients computed at multiple scales. We combine this technique with the results of our previous wavelets-based CAD algorithm for detecting microcalcifications.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Reproducibility of an automated scheme for the detection of clustered microcalcifications on digital mammograms

Abstract: Computer-aided diagnosis can be defined as a diagnosis made by a radiologist who takes into account the computerized analysis of the radiograph. The potential advantage of this approach is that errors by human observers that are caused by intra-observer variation, can be caught by the computer, which performs a thorough, methodical search of the image. However, if the input image to computer comes from a digitized radiograph, then the process of digitization introduces variability into the computer analysis of the image. Because the film digitizer samples the image, re-digitization will not necessarily produce the exact same digital image, and subsequently, the computerized scheme may produce different results on the different samples of the original image. The purpose of this study was to examine the amount of variability introduced by film digitization by measuring the reproducibility of our computerized scheme for the detection of clustered microcalcifications on mammograms when the mammogram is digitized a number of times. We have found in general that if the detected cluster (either a true or false cluster) corresponds to some obvious anatomical structure, then the cluster will be re-detected upon re-digitization. If, however, the cluster corresponds to low contrast objects within the breast, including image noise, then the cluster is not likely to be re- detected. As a result, true clusters tend to be much more reproducible than false-positive clusters. In the future, when direct digital radiographs are used as input to the computerized schemes, problems with reproducibility will not exist.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Comparison of contrast detail curves of full field digital with screen film breast phantom images

Abstract: In this investigation, we imaged a standard breast phantom and compared the contrast detail curves from a prototype full breast digital mammography system with the corresponding curves for a conventional, analog screen-film system. The full breast digital system exhibited superior contrast detail detectability. The results from this study will be used to plan future clinical evaluations comparing full breast digital and screen film mammography.

Development of a Common Database for Digital Mammography Research

Abstract: : The purpose of this infrastructure project is to develop a large database of digitized mammograms that will be distributed free of charge to researchers working in all aspects of digital mammography This database will facilitate and promote rapid development in digital mammography research The database will consist of 1000 cases subdivided into 5 categories, 4 containing different breast lesions -- masses, microcalcifications, architectural distortions, asymmetric densities (both benign and malignant) -- and one containing normal mammograms The mammograms will be collected and digitized (005-mm pixel size) at two sites: the Universities of Chicago and North Carolina The database will be stored at the two sites and will be available over internet, and by mail on CD, tape, and magneto-optical disks To date 630 cases have been digitized Each case consists of index and previous exams (each having four standard views) and up to two special-view mammograms (eg, magnification views) The computer systems for the database have been assembled and are connected to the network The first release of 50 cases with clustered microcalcifications will be made shortly after true location of the cluster is determined This release will be followed by another 50 cases of microcalcifications and 100 cases with masses Along with the images, instructions on how to use the database will also be distributed This includes an objective scoring method that we are developing based on input from radiologists'

Computerized Diagnostics In Digital Mammography

Abstract: Mammography is a major diagnostic procedure in early detection of breast cancer; however, the interpretation of mammograms for diagnosis of breast cancer can be problematic. A computerized diagnostic system has been developed to serve as a "second opinion" for radiologists. This system enhances the structures which appear in the mammogram and calculates parameters which characterize lesions. The authors have deevloped special versions for statistical classification and discrimination of mammographic lesions. Algorithms of recognition of lesions were constructed and examined on mammographic lesions with proven pathology.

A statistical representation of pattern structure for digital mammography.

Abstract: 1. INTRODUCTION Mammograms are complex in appearance and early signs of disease are often small or subtle. Malignant lesions frequently reveal their presence to the radiologist only by subtle changes to the surrounding tissue [1]. This results in a distorted, abnormal pattern of linear structures. Architectural distortions and stellate lesions are examples of abnormal patterns, frequently presenting with a focused appearance of radiating linear structures. Research to date has shown the importance of certain image features such as radiating linear structure concurrency, spread of focus and radial distance [2,3,4]. However, attempts to automatically detect these abnormalities have concentrated solely on the detection of the known features followed by an ad-hoc heuristic approach to the combination of feature evidence. We present an alternative compact representation of pattern structure that completely encapsulates all patterns yet remains uncommitted to specific types of pattern.Our representation places no emphasis upon the known features yet clearly incorporates them. 2.SYNTHETIC DATA To obtain a clear understanding of the statistical line pattern representation synthetic patterns were generated to train and evaluate the models. An example pattern is shown in figure 1.

Digital mammography scanner: performance characteristics and preliminary clinical results

Abstract: Presents an introductory system design analysis for a novel digital mammography system. The design approach taken is based on the scanning detector composed of a linear assembly of bonded modules. Each module is built by attaching to a fiber optics taper a charge coupled device (CCD) optical sensor operating in the time-delay-and-integrate (TDI) mode dictated by the constant velocity scanning of the detector assembly. The X-ray entrance surface of the taper is covered with a scintillator. Results obtained with a detector 18 cm long and 1 cm wide, with limiting resolution of approximately 9 cy/mm are presented to demonstrate the viability of this design approach for digital mammography. (7 pages)

Dual-energy in mammography: feasibility study

Abstract: The purpose of this work is to examine the feasibility of dual-energy techniques to enhance the detection of microcalcifications in digital mammography. The digital mammography system used in this study consists of two different mammography systems; one is the conventional mammography system with molybdenum target and Mo filtration and the other is the clinical version of a low dose x-ray system with tungsten target and aluminum filtration. The low dose system is optimized for screen-film mammography with a highly efficient scatter rejection device built by Fischer Imaging Systems for evaluation at NIH. The system was designed by the University of Southern California based on multiparameter optimization techniques. Prototypes of this system have been constructed and evaluated at the Center for Devices and Radiological Health. The digital radiography system is based on the Fuji 9000 computed radiography (CR) system which uses a storage phosphor imaging plate as the receptor. High resolution plates (HR-V) are used in this study. Dual-energy is one technique to reduce the structured noise associated with the complexity of the background of normal anatomy surrounding a lesion. This can be done by taking the advantage of the x-ray attenuation characteristics of two different structures such as soft tissue and bone in chest radiography. We have applied this technique to the detection of microcalcifications in mammography. The overall system performance based on this technique is evaluated. Results presented are based on the evaluation of phantom images.

Fuzzy logic in digital mammography: analysis of lobulation

Abstract: This paper illustrates how the fuzzy logic approach can be used to formalize the American College of Radiology (ACR) breast imaging reporting lexicon. In current practice radiologists make a relatively subjective determination for many terms from the lexicon related to breast cancer diagnosis. Lobulation and microlobulation of nodules are important features in breast cancer diagnosis based on mammographic analysis by using the ACR lexicon. We offer an approach for formalizing the distinction of these features and also formalize the description of the intermediate cases between lobulated and microlobulated masses. In this paper it is shown that fuzzy logic can be an effective tool in dealing with this kind of problems. The proposed formalization creates a base for the next two steps: (i) the automatic extraction of the related primitives from the image, and (ii) the detection of lobulated and microlobulated masses based on these primitives.

Earlier detection of interval breast cancers with adaptive neighborhood contrast enhancement of mammograms

Abstract: Breast cancer is a leading cause of death among women. Mammography is the best established procedure for breast cancer screening and diagnosis. However, mammograms are hard to interpret even by highly-qualified radiologists, especially in cancers at their early stages. In this paper, we analyze the effectiveness of our adaptive neighborhood contrast enhancement (ANCE) technique in increasing breast cancer diagnosis sensitivity. Two hundred and thirty- three film-screen mammograms of twenty-eight interval cancer patients and six benign control cases were digitized with high-resolution of about 4096 by 2048 by 10-bit pixels and then processed with our ANCE method. Unprocessed and processed digitized mammograms as well as the original films were presented to three reference radiologists for a receiver operating characteristic (ROC) evaluation. The results show that the radiologists' performance with the ANCE-processed images is the best among the three sets of images (original, digitized, and enhanced) in terms of area under the ROC curve, and that diagnostic sensitivity is improved by our ANCE algorithm. All of the 19 interval cancer cases not detected with original films of earlier mammography tests were diagnosed as malignant with the corresponding ANCE- processed versions, while only one of six benign patients initially labeled correctly with the original mammograms was interpreted as malignant after enhancement. This study demonstrates the potential of diagnostic performance improvement for early detection of breast cancer with proper digital image enhancement.© (1996) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.