Educational technology in medical imaging education

Purpose The emergence of digital technologies has created enthusiasm for their application to student learning. An evolving issue in medical imaging is how these technologies might be implemented within programs. Method A review of the literature was performed to explore applications and issues of educational technology in medical imaging Results There are a range of applications for educational technology within medical imaging education however limitations do exist. Learners must be supported by the development of skills to utilize education technologies. The digital picture archival and communication environment presents an ideal opportunity to enhance student learning through interaction and engagement with images. Implementation of education technologies to support student placement activities is an area for future development provided equity of access is addressed. Conclusion Education technologies have specific application to medical imaging education as part of a blended curriculum.

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

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

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

Annual report /

Description based on: 1983-84; title from cover.

Biennial report /

Title from cover.

Integration of medical images to the teaching of systematic pathology : an evaluation of relevance

A sound knowledge of pathological disease processes is required for professional practice within health professions. The project described in this paper reviewed the resources currently available for the delivery of systematic pathology tutorials. Additional complementary resources were developed and the inclusion of these additional learning resources in practical tutorial sessions was evaluated for their impact on student learning. Student evaluation of the learning resources was undertaken across one semester with two different cohorts of health profession students using questionnaires and focus group discussion. Both cohorts reported an enhancement to their understanding of pathological disease processes through the use of the additional resources. Results indicate student perception of the value of the resources correlates with staff perception and is independent of prior experiences.

The development and evaluation of a medical imaging training immersive environment

Introduction A novel realistic 3D virtual reality (VR) application has been developed to allow medical imaging students at Queensland University of Technology to practice radiographic techniques independently outside the usual radiography laboratory. Methods A flexible agile development methodology was used to create the software rapidly and effectively. A 3D gaming environment and realistic models were used to engender presence in the software while tutor-determined gold standards enabled students to compare their performance and learn in a problem-based learning pedagogy. Results Students reported high levels of satisfaction and perceived value and the software enabled up to 40 concurrent users to prepare for clinical practice. Student feedback also indicated that they found 3D to be of limited value in the desktop version compared to the usual 2D approach. A randomised comparison between groups receiving software-based and traditional practice measured performance in a formative role play with real equipment. The results of this work indicated superior performance with the equipment for the VR trained students (P = 0.0366) and confirmed the value of VR for enhancing 3D equipment-based problem-solving skills. Conclusions Students practising projection techniques virtually performed better at role play assessments than students practising in a traditional radiography laboratory only. The application particularly helped with 3D equipment configuration, suggesting that teaching 3D problem solving is an ideal use of such medical equipment simulators. Ongoing development work aims to establish the role of VR software in preparing students for clinical practice with a range of medical imaging equipment.

Exploring the use of the Swiss medical tariffication codes (TARMED) in the establishment of the frequency of radiodiagnostic examinations.

In population surveys of the exposure to medical X-rays both the frequency of examinations and the effective dose per examination are required. The use of the Swiss medical tariffication system (TARMED) for establishing the frequency of X-ray medical examinations was explored. The method was tested for radiography examinations performed in 2008 at the Lausanne University Hospital. The annual numbers of radiographies determined from the "TARMED" database are in good agreement with the figures extracted from the local RIS (Radiology Information System). The "TARMED" is a reliable and fast method for establishing the frequency of radiography examination, if we respect the context in which the "TARMED" code is used. In addition, this billing context provides most valuable information on the average number of radiographs per examination as well as the age and sex distributions. Radiographies represent the major part of X-ray examinations and are performed by about 4,000 practices and hospitals in Switzerland. Therefore this method has the potential to drastically simplify the organisation of nationwide surveys. There are still some difficulties to overcome if the method is to be used to assess the frequency of computed tomography or fluoroscopy examinations; procedures that deliver most of the radiation dose to the population. This is due to the poor specificity of "TARMED" codes concerning these modalities. However, the use of CT and fluoroscopy installations is easier to monitor using conventional survey methods since there are fewer centres. Ways to overcome the "TARMED" limitations for these two modalities are still being explored.

Genotoxic effects of X-rays on keratinized mucosa cells during panoramic dental radiography

Objectives: The aim of this study was to evaluate the genotoxic effects of X-rays on epithelial gingival cells during panoramic dental radiography using a differentiated protocol for the micronucleus test. Methods: 40 healthy individuals who underwent this procedure for diagnostic purposes on request from their dentists agreed to participate in this study. All of them answered a questionnaire before the examination. Epithelial gingival cells were obtained from the keratinized mucosa of the upper dental arcade by gentle scraping with a cervical brush immediately before exposure and 10 days later. Cytological preparations were stained according to the Feulgen-Rossenbeck reaction, counterstained with fast green 1% for 1 min and analysed under a light microscope. Micronuclei, nuclear projections (broken eggs) and degenerative nuclear alterations (pyknosis, karyolysis, karyorrhexis and condensed chromatin) were scored. Results: The frequency of micronuclei was significantly higher after exposure (P < 0.05), as were frequencies of nuclear alterations indicate of apoptosis (P < 0.001). Conclusions: These results indicate that X-ray radiation emitted during panoramic dental radiography induces a genotoxic effect on epithelial gingival cells that increases the frequency of chromosomal damage and nuclear alterations indicative of apoptosis.

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.