Microcalcification evaluation in computer assisted diagnosis for digital mammography

In order to develop applications for z;isual interpretation of medical images, the early detection and evaluation of microcalcifications in digital mammograms is verg important since their presence is often associated with a high incidence of breast cancers. Accurate classification into benign and malignant groups would help improve diagnostic sensitivity as well as reduce the number of unnecessa y biopsies. The challenge here is the selection of the useful features to distinguish benign from malignant micro calcifications. Our purpose in this work is to analyse a microcalcification evaluation method based on a set of shapebased features extracted from the digitised mammography. The segmentation of the microcalcifications is performed using a fixed-tolerance region growing method to extract boundaries of calcifications with manually selected seed pixels. Taking into account that shapes and sizes of clustered microcalcifications have been associated with a high risk of carcinoma based on digerent subjective measures, such as whether or not the calcifications are irregular, linear, vermiform, branched, rounded or ring like, our efforts were addressed to obtain a feature set related to the shape. The identification of the pammeters concerning the malignant character of the microcalcifications was performed on a set of 146 mammograms with their real diagnosis known in advance from biopsies. This allowed identifying the following shape-based parameters as the relevant ones: Number of clusters, Number of holes, Area, Feret elongation, Roughness, and Elongation. Further experiments on a set of 70 new mammogmms showed that the performance of the classification scheme is close to the mean performance of three expert radiologists, which allows to consider the proposed method for assisting the diagnosis and encourages to continue the investigation in the sense of adding new features not only related to the shape

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

Digital radiography using digital detector arrays fulfills critical applications for offshore pipelines

Digital radiography in the inspection of welded pipes to be installed under deep water offshore gas and oil pipelines, like a presalt in Brazil, in the paper has been investigated. The aim is to use digital radiography for nondestructive testing of welds as it is already in use in the medical, aerospace, security, automotive, and petrochemical sectors. Among the current options, the DDA (Digital Detector Array) is considered as one of the best solutions to replace industrial films, as well as to increase the sensitivity to reduce the inspection cycle time. This paper shows the results of this new technique, comparing it to radiography with industrial films systems. In this paper, 20 test specimens of longitudinal welded pipe joints, specially prepared with artificial defects like cracks, lack of fusion, lack of penetration, and porosities and slag inclusions with varying dimensions and in 06 different base metal wall thicknesses, were tested and a comparison of the techniques was made. These experiments verified the purposed rules for parameter definitions and selections to control the required digital radiographic image quality as described in the draft international standard ISO/DIS 10893-7. This draft is first standard establishing the parameters for digital radiography on weld seam of welded steel pipes for pressure purposes to be used on gas and oil pipelines.

Evaluation of simulated external root resorptions with digital radiography and digital subtraction radiography

Introduction: Root resorption can cause damage in orthodontic patients. Digital subtraction radiography (DSR) is a useful resource for the detection of mineral losses. The purpose of this study was to compare the efficacy of digital radiography (DR) and DSR in detecting simulated external root resorption. Examiner agreement between the 2 techniques was also evaluated. Methods: Root resorptions of various sizes were simulated on the apical and lingual aspects of 49 teeth from 9 dry human mandibles. The teeth were radiographed in standardized conditions. The radiographs were registered with Regeemy Image Registration and Mosaicking (version 0.2.43-RCB, DPI-INPE, Sao Jose dos Campos, São Paulo, Brazil) and subtracted with Image Tool (University of Texas Health Science Center at San Antonio). The subtracted images and the digital radiographs were evaluated by 3 oral radiologists. Results: No statistically significant differences were found for the methods in the detection of apical root resorptions, independently from lesion size, and of lingual resorptions of 1.2 mm or greater. DSR was significantly better than DR for detection of lingual resorptions up to 1 mm. Resorptions less than 0.5 mm were not precisely detected by either method. DSR provided better intraexaminer and interexaminer agreement than did DR. Conclusions: Both methods are precise for detection of apical root resorptions as small as 0.5 mm and lingual resorptions of 1 mm or more. However, DSR frequently performed better than did DR. (Am J Orthod Dentofacial Orthop 2011;139:324-33)

Investigation of digital techniques for radar land mass simulation.

Cover title.

The use of digital techniques for flight control; a discussion prepared for SAE Committee A-18 on Aerospace Vehicle Flight Control Systems.

Mode of access: Internet.

Nonlinearity compensation in multi-rate 28 Gbaud WDM systems employing optical and digital techniques under diverse link configurations

Digital back-propagation (DBP) has recently been proposed for the comprehensive compensation of channel nonlinearities in optical communication systems. While DBP is attractive for its flexibility and performance, it poses significant challenges in terms of computational complexity. Alternatively, phase conjugation or spectral inversion has previously been employed to mitigate nonlinear fibre impairments. Though spectral inversion is relatively straightforward to implement in optical or electrical domain, it requires precise positioning and symmetrised link power profile in order to avail the full benefit. In this paper, we directly compare ideal and low-precision single-channel DBP with single-channel spectral-inversion both with and without symmetry correction via dispersive chirping. We demonstrate that for all the dispersion maps studied, spectral inversion approaches the performance of ideal DBP with 40 steps per span and exceeds the performance of electronic dispersion compensation by ~3.5 dB in Q-factor, enabling up to 96% reduction in complexity in terms of required DBP stages, relative to low precision one step per span based DBP. For maps where quasi-phase matching is a significant issue, spectral inversion significantly outperforms ideal DBP by ~3 dB.

Digital radiography for the inspection of weld seams of pipelines - better sensitivity

Conventional radiography, using industrial radiographic films, has its days numbered. Digital radiography, recently, has taken its place in various segments of products and services, such as medicine, aerospace, security, automotive, etc. As well as the technological trend, the digital technique has brought proven benefits in terms of productivity, sensitivity, the environment, tools for image treatment, cost reductions, etc. If the weld to be inspected is on a serried product, such as, for example, a pipe, the best option for the use of digital radiography is the plane detector, since its use can reduce the length of the inspection cycle due to its high degree of automation. This work tested welded joints produced with the submerged arc process, which were specially prepared in such a way that it shows small artificial cracks, which served as the basis forcomparing the sensitivity levels of the techniques involved. After carrying out the various experiments, the digital meth odshowed the highest sensitivity for the image quality indicator (IQI) of the wire and also in terms of detecting small discontinuities, indicating that the use of digital radiography using the plane detector had advantages over the conventional technique (Moreira et al. Digital radiography, the use of plane detectors for the inspection of welds in oil pipes and gas pipes.9th COTEQ and XXV National Testing Congress for Non Destructive Testing and Inspection; Salvador, Bahia, Brazil and Bavendiek et al. New digital radiography procedure exceeds film sensitivity considerably in aerospace applications. ECNDT; 2006; Berlin). The works were carried out on the basis of the specifications for oil and gas pipelines, API 5L 2004 edition (American Petroleum Institute. API 5L: specification for line pipe. 4th ed. p. 155; 2004) and ISO 3183 2007 edition (International Organization for Standardization, ISO 3183. Petroleum and gas industries - steel pipes for pi pelines transportation systems. p. 143; 2007). © 2010 Taylor & Francis.