Mammography

In this volume, the topics are constructed from a variety of contents: the bases of mammography systems, optimization of screening mammography with reference to evidence-based research, new technologies of image acquisition and its surrounding systems, and case reports with reference to up-to-date multimodality images of breast cancer. Mammography has been lagged in the transition to digital imaging systems because of the necessity of high resolution for diagnosis. However, in the past ten years, technical improvement has resolved the difficulties and boosted new diagnostic systems. We hope that the reader will learn the essentials of mammography and will be forward-looking for the new technologies. We want to express our sincere gratitude and appreciation?to all the co-authors who have contributed their work to this volume

Computer-aided detection and diagnosis of breast cancer in 2D and 3D medical imaging through multifractal analysis

This Thesis describes the research work performed in the scope of a doctoral research program and presents its conclusions and contributions. The research activities were carried on in the industry with Siemens S.A. Healthcare Sector, in integration with a research team. Siemens S.A. Healthcare Sector is one of the world biggest suppliers of products, services and complete solutions in the medical sector. The company offers a wide selection of diagnostic and therapeutic equipment and information systems. Siemens products for medical imaging and in vivo diagnostics include: ultrasound, computer tomography, mammography, digital breast tomosynthesis, magnetic resonance, equipment to angiography and coronary angiography, nuclear imaging, and many others. Siemens has a vast experience in Healthcare and at the beginning of this project it was strategically interested in solutions to improve the detection of Breast Cancer, to increase its competitiveness in the sector. The company owns several patents related with self-similarity analysis, which formed the background of this Thesis. Furthermore, Siemens intended to explore commercially the computer- aided automatic detection and diagnosis eld for portfolio integration. Therefore, with the high knowledge acquired by University of Beira Interior in this area together with this Thesis, will allow Siemens to apply the most recent scienti c progress in the detection of the breast cancer, and it is foreseeable that together we can develop a new technology with high potential. The project resulted in the submission of two invention disclosures for evaluation in Siemens A.G., two articles published in peer-reviewed journals indexed in ISI Science Citation Index, two other articles submitted in peer-reviewed journals, and several international conference papers. This work on computer-aided-diagnosis in breast led to innovative software and novel processes of research and development, for which the project received the Siemens Innovation Award in 2012. It was very rewarding to carry on such technological and innovative project in a socially sensitive area as Breast Cancer.No cancro da mama a deteção precoce e o diagnóstico correto são de extrema importância na prescrição terapêutica e caz e e ciente, que potencie o aumento da taxa de sobrevivência à doença. A teoria multifractal foi inicialmente introduzida no contexto da análise de sinal e a sua utilidade foi demonstrada na descrição de comportamentos siológicos de bio-sinais e até na deteção e predição de patologias. Nesta Tese, três métodos multifractais foram estendidos para imagens bi-dimensionais (2D) e comparados na deteção de microcalci cações em mamogramas. Um destes métodos foi também adaptado para a classi cação de massas da mama, em cortes transversais 2D obtidos por ressonância magnética (RM) de mama, em grupos de massas provavelmente benignas e com suspeição de malignidade. Um novo método de análise multifractal usando a lacunaridade tri-dimensional (3D) foi proposto para classi cação de massas da mama em imagens volumétricas 3D de RM de mama. A análise multifractal revelou diferenças na complexidade subjacente às localizações das microcalci cações em relação aos tecidos normais, permitindo uma boa exatidão da sua deteção em mamogramas. Adicionalmente, foram extraídas por análise multifractal características dos tecidos que permitiram identi car os casos tipicamente recomendados para biópsia em imagens 2D de RM de mama. A análise multifractal 3D foi e caz na classi cação de lesões mamárias benignas e malignas em imagens 3D de RM de mama. Este método foi mais exato para esta classi cação do que o método 2D ou o método padrão de análise de contraste cinético tumoral. Em conclusão, a análise multifractal fornece informação útil para deteção auxiliada por computador em mamogra a e diagnóstico auxiliado por computador em imagens 2D e 3D de RM de mama, tendo o potencial de complementar a interpretação dos radiologistas

BREAST CANCER RISK AND DETECTION USING GENES, MAMMOGRAPHIC DENSITY AND MAMMOGRAMS

Ph.DDOCTOR OF PHILOSOPH

Quantification and segmentation of breast cancer diagnosis: efficient hardware accelerator approach

The mammography image eccentric area is the breast density percentage measurement. The technical challenge of quantification in radiology leads to misinterpretation in screening. Data feedback from society, institutional, and industry shows that quantification and segmentation frameworks have rapidly become the primary methodologies for structuring and interpreting mammogram digital images. Segmentation clustering algorithms have setbacks on overlapping clusters, proportion, and multidimensional scaling to map and leverage the data. In combination, mammogram quantification creates a long-standing focus area. The algorithm proposed must reduce complexity and target data points distributed in iterative, and boost cluster centroid merged into a single updating process to evade the large storage requirement. The mammogram database's initial test segment is critical for evaluating performance and determining the Area Under the Curve (AUC) to alias with medical policy. In addition, a new image clustering algorithm anticipates the need for largescale serial and parallel processing. There is no solution on the market, and it is necessary to implement communication protocols between devices. Exploiting and targeting utilization hardware tasks will further extend the prospect of improvement in the cluster. Benchmarking their resources and performance is required. Finally, the medical imperatives cluster was objectively validated using qualitative and quantitative inspection. The proposed method should overcome the technical challenges that radiologists face

Intelligent computing applications based on eye gaze : their role in mammographic interpretation training

Early breast cancer in women is best identified through high quality mammographic screening. This is achieved by well trained health professionals and appropriate imaging. Traditionally this has used X-ray film but is rapidly changing to utilise digital imaging with the resultant mammograms visually examined on high resolution clinical workstations. These digital images can also be viewed on a range of display devices, such as standard computer monitors or PDAs. In this thesis the potential of using such non-clinical workstation display devices for training purposes in breast screening has been investigated. The research introduces and reviews breast screening both in the UK and internationally where it concentrates upon China which is beginning screening. Various imaging technologies used to examine the breast are described, concentrating upon the move from using X-ray film to digital mammograms. Training in screening in the UK is detailed and it is argued that there is a need to extend this. Initially, a national survey of all UK mammography screeners within the National Health Breast Screening Programme (NHSBSP) was undertaken. This highlighted the current main difficulties of mammographic (film) interpretation training being tied to the device for inspecting these images. The screeners perceived the need for future digital imaging training that could be outside the breast screening centre; namely 3W training (Whatever training required, Whenever and Wherever). This is largely because the clinical workstations would logistically not be available for training purposes due to the daily screening demand. Whilst these workstations must be used for screening and diagnostic purposes to allow visualisation of very small detail in the images, it is argued here that training to identify such features can be undertaken on other devices where there is not the time constraints that exist during breast screening. A series of small pilot studies were then undertaken, trialling experienced radiologists with potential displays (PDAs and laptops) for mammographic image examination. These studies demonstrated that even on a PDA small mammographic features could be identified, albeit with difficulty, even with a very limited HCI manipulation tool. For training purposes the laptop, studied here with no HCI tool, was supported. Such promising results of display acceptability led to an investigation of mammographic inspection on displays of various sizes and resolutions. This study employed radiography students, potentially eventual screeners, who were eye tracked as they examined images on various sized displays. This showed that it could be possible to use a small PDA to deliver training. A detailed study then investigated whether aspects of an expert radiologist s visual inspection behaviour could be used to develop various training approaches. Four approaches were developed and examined using naïve observers who were eye tracked as they were trained and tested. The approaches were found to be all feasible to implement but of variable usefulness for delivering mammographic interpretation training; this was confirmed by opinions from a focus group of screeners. On the basis of the previous studies, over a period of eight months, a large scale study involving 15 film readers from major breast screening centres was conducted where they examined series of digital mammograms on a clinical workstation, monitor and an iPhone. Overall results on individuals performance, image manipulation behaviour and visual search data indicated that a standard monitor could be employed successfully as an alternative for the digital workstation to deliver on-demand mammographic interpretation training using the full mammographic case images. The small iPhone, elicited poor performance, and was therefore judged not suitable for delivering training with the software employed here. However, future software developments may well overcome its shortcomings. The potential to implement training in China was examined by studying the current skill level of some practicing radiologists and an examination of how they responded to the developed training approaches. Results suggest that such an approach would be also applicable in other countries with different levels of screening skills. On-going further work is also discussed: the improvement of performance evaluation in mammography; new visual research on other breast imaging modalities and using visual search with computer aided detection to assist mammographic interpretation training.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Methodology for taking a computer-aided breast cancer screening system from the laboratory to the marketplace

Breast cancer is one of the most common causes of death in women, and yet is one of the more 'curable' cancers if caught early. Since its inception in 1987, the Breast Screening Programme has been the principal tool in the National Health Service's fight to reduce the number of cancer related deaths in the UK. Breast screening using mammography is widely viewed as the most effective way of detecting early breast cancer, with the UK population of women over the age of 50 being invited to a screening session every three years. However, national shortages of clinical staff willing to enter and remain in this field mean that the NHS Breast Screening Programme is severely understaffed. This thesis discusses one way in which technology can assist in the screening programme; specifically, the use of a computer-aided cancer detection system. Here, we will present the design and analysis of a sequence of experiments used to develop and evaluate such a system. PROMAM (PROmpting for MAMmography) involved the scanning and digitising of mammograms, and the subsequent analysis of the digital image by a series of algorithms. Initial evaluation was done to ensure that the algorithms were performing satisfactorily at a technical level before being introduced into a clinical setting. Two large experiments with the algorithms were designed and evaluated: 1. offering radiologists three levels of algorithm prompting and, as a control, an unprompted level, on samples of mammographic films, with outcomes being their recall rate and subjective views at each prompting level, 2. a pre-clinical experiment, conducted under semi-clinical conditions, where two readers would see a batch of films seeded with higher than normal numbers of cancers, with readers allocated randomly to prompted and unprompted views of films. The first experiment was designed using a Graeco-Latin Square, with three 'nuisance' variables and the treatment factor of prompting levels (no prompts, low level of prompt¬ ing, medium and high). Four radiologists read at each level of prompting once, on dif¬ ferent sets of films. One of the more interesting results was that the recall rate did not increase as the prompting rate rose - contrary to prior expectations. Most of the differ¬ ences seen between the prompting rates could be explained as radiologist differences. Once these were taken into account, the level of prompting had little effect. Addition¬ ally, although the time taken to read a set of films increased as the prompting rate increased (as would be expected), it was only an increase of 26% from the unprompted set to the set with the highest number of prompts. Observational data suggested that the lowest level of prompting was not maintaining the interest of the radiologist, thus leading them to neglect the prompts. The following experiment moved the system a step closer to a true clinical demonstra¬ tion of the efficacy of PROMAM, being conducted under semi-clinical conditions. Using a method of minimisation, the number of cancers each radiologist viewed as first reader, second reader, prompted or unprompted were balanced. Preliminary exploratory anal¬ ysis indicated that the recall rate declined with the introduction of the prompting system, but more detailed, analysis indicated that much of this difference was due to a radiologist effect. Although cancer detection was slightly lower with the prompting system, examination of the 11 cancers missed by the prompted radiologist showed that six of these had been correctly prompted by the algorithms. This demonstrated scope to improve the cancer detection rate by nearly 5%. These experiments determined the 'production' version of the prompting system. A design to evaluate the system in a sample of 100,000 women in six centres was produced, but due to circumstances beyond the project team's control, it was not possible to take this work to the stage of a full 'trial' of the system. The design concept can, however, apply to the evaluation of any similar prompting system. The recommended design is therefore presented, together with an analysis of data from a simulated application of this design. This simulation has allowed recommendations to be made on the most appropriate ways to analyse the extensive and complicated dataset that will be obtained. In particular, it identified technical problems that can arise from the application on one candidate analytical method, and an explanation for the failure obtained It is quite clear from the evidence presented in this thesis that there is much scope for improvement in the cancer detection rate by the use of a prompting system, with¬ out a corresponding loss in the specificity. With the shortage of radiologists and ra¬ diographers, and the increasing demand placed on the Breast Screening Programme, technology could play a beneficial role in screening for breast cancer in the coming year

Computer-aided diagnosis in mammography : correlation of regions in multiple standard mammographic views of the same breast.

Thesis (Ph.D.)-University of KwaZulu-Natal, 2006.Abstract available in PDF file