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

Aplicación de herramientas estereológicas y de cuantificación no lineal al estudio de la distribución, isotropía y tamaño del lecho microvascular en próstata normal y patológica

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Facultad de Medicina, Departamento de Cirugía. Fecha de lectura: 8 de Junio de 2012

Cell-Matrix Adhesion in Muscle Development and Disease

A variety of diseases, both inherited and acquired, affect muscle tissues in humans. The anchoring of muscle fibers to their surrounding environment is critical for muscle homeostasis. Muscle fibers attach to their microenvironment through cell-matrix adhesion complexes. These anchoring complexes are placed under repeated stress during muscle contraction. Genetic mutations in these complexes weaken the attachment between muscle fibers and their microenvironment, making fibers more susceptible to damage and death. This increased fiber degeneration eventually leads to progressive muscle wasting diseases, known as congenital muscular dystrophies. Although clinical trials are ongoing, there is presently no way to cure the loss of muscle structure and function associated with congenital muscular dystrophies.Animal models of human diseases are used to gain insights into mechanisms of disease pathogenesis and to screen for potential therapeutic compounds. The zebrafish CELL-MATRIX ADHESION IN MUSCLE model system, well-known for its use in developmental biological studies, is rapidly becoming widely-accepted as a useful model for biomedical research. We utilized zebrafish embryos to study the initial morphogenesis of substructures in the muscle microenvironment and the initial stable cell-matrix adhesions formed in muscle tissue. As the muscle fiber microenvironment is abnormal in congenital muscular dystrophies and cell-matrix adhesions are weakened, studies elucidating how strong, stable cell-matrix adhesions form in development could be informative in the effort to treat congenital muscular dystrophies.Using this approach, we identified a previously undescribed cell-matrix adhesion pathway required for normal organization of an important substructure in the muscle tissue microenvironment. We show that activation of this cell-matrix adhesion pathway in dystrophic zebrafish not only significantly reduces muscle degeneration, but also improves swimming ability. The results presented in this dissertation identify proteins that function in this cell-matrix adhesion pathway and use dystrophic zebrafish to show the benefits and limitations of this pathway in treating symptoms of congenital muscular dystrophies. Our findings suggest that activation of this pathway has the potential to ameliorate loss of muscle structure and function in multiple muscular dystrophies

Creating the Future: Research and Technology

With the many different technical talents, Marshall Space Flight Center (MSFC) continues to be an important force behind many scientific breakthroughs. The MSFC's annual report reviews the technology developments, research in space and microgravity sciences, studies in space system concepts, and technology transfer. The technology development programs include development in: (1) space propulsion and fluid management, (2) structures and dynamics, (3) materials and processes and (4) avionics and optics

2015 Oklahoma Research Day Full Program

This document contains all abstracts from the 2015 Oklahoma Research Day held at Northeastern State University