A Critical Examination of Two Specific Approaches Used to Characterize Medical Images: i) Projection-based Descriptors for Image Retrieval and ii) Estimating Fractal Dimensions of Discrete Sets

In this thesis we provide a critical examination of two methods which are used to characterize medical images. Accordingly, this thesis is split into two main parts. First, we take a look at the problem of designing efficient, compact image descriptors for content-based image retrieval of digital histopathology slides. Our approach here is twofold, in that we propose a frequency-based approach to encoding projection gradients and we study the effect of separating histology slides into two colour components based on a typical staining protocol. Our frequency-based approach is shown to be more effective in terms of search performance and efficiency than the standard MinMax method of binary encoding often employed in the literature. Furthermore, we find that by separating histopathology images into their stain components, we see a significant improvement in search accuracy over the use of greyscale images, and comparable, and often superior performance to the use of three channel RGB colour images as inputs. The results in this part of the thesis not only stand on their own as a solution for image search, they can also be applied to improve the efficiency and performance of future research in this field. In the second part of this thesis, we consider the use of fractal dimensions as a method to characterize vascular networks, and other branching structures such as streams, and trees. We discuss the self-similarity (or lack thereof) of branching structures, and provide a clear argument against the use of the typical methods, such as the box-counting and sandbox methods, to estimate fractal dimensions from finite images of branching networks. Additionally, local slopes are used as a tool to illustrate the issues with these approaches when they are applied to branching structures, such as computer-generated fractal trees and retinal vascular networks. Some alternative approaches are suggested which could be used for the characterization of complex branching structures, including vascular networks

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

Tailoring vessel morphology in vivo

Tissue engineering is a rapidly growing field which seeks to provide alternatives to organ transplantation in order to address the increasing need for transplantable tissues. One huge hurdle in this effort is the provision of thick tissues; this hurdle exists because currently there is no way to provide prevascularized or rapidly vascularizable scaffolds. To design thick, vascularized tissues, scaffolds are needed that can induce vessels which are similar to the microvasculature found in normal tissues. Angiogenic biomaterials are being developed to provide useful scaffolds to address this problem. In this thesis angiogenic and cell signaling and adhesion factors were incorporated into a biomimetic poly(ethylene glycol) (PEG) hydrogel system. The composition of these hydrogels was precisely tuned to induce the formation of differing vessel morphology. To sensitively measure induced microvascular morphology and to compare it to native microvessels in several tissues, this thesis developed an image-based tool for quantification of scale invariant and classical measures of vessel morphology. The tool displayed great utility in the comparison of native vessels and remodeling vessels in normal tissues. To utilize this tool to tune the vessel response in vivo , Flk1::myr-mCherry fluorescently labeled mice were implanted with Platelet Derived Growth Factor-BB (PDGF-BB) and basic Fibroblast Growth Factor (FGF-2) containing PEG-based hydrogels in a modified mouse corneal angiogenesis assay. Resulting vessels were imaged with confocal microscopy, analyzed with the image based tool created in this thesis to compare morphological differences between treatment groups, and used to create a linear relationship between space filling parameters and dose of growth factor release. Morphological parameters of native mouse tissue vessels were then compared to the linear fit to calculate the dose of growth factors needed to induce vessels similar in morphology to native vessels. Resulting induced vessels did match in morphology to the target vessels. Several other covalently bound signals were then analyzed in the assay and resulting morphology of vessels was compared in several studies which further highlighted the utility of the micropocket assay in conjunction with the image based tool for vessel morphological quantification. Finally, an alternative method to provide rapid vasculature to the constructs, which relied on pre-seeded hydrogels encapsulated endothelial cells was also developed and shown to allow anastamosis between induced host vessels and the implanted construct within 48 hours. These results indicate great promise in the rational design of synthetic, bioactive hydrogels, which can be used as a platform to study microvascular induction for regenerative medicine and angiogenesis research. Future applications of this research may help to develop therapeutic strategies to ameliorate human disease by replacing organs or correcting vessel morphology in the case of ischemic diseases and cancer

Modification of fractal analysis of neuron digital images morphology of some human brain nuclei and histopathological samples of breast tumor

Kompleksnost i neregularnost objekata koji se sreću u medicinskim istraživanjima pokazuju potrebu za pronalaženjem novih adekvatnih načina opisivanja i za usavršavanjem postojećih metoda. Korist ovakvih novih metoda se ističe u boljoj klasifikaciji i razumevanju funkcije različitih fizioloških pojava i tkiva, kao i u dijagnostikovanju i prognozama rizika nekih oboljenja. Fraktalna analiza se pokazala kao korisno sredstvo u ove svrhe. Glavne teme ove teze su modifikacija i usavršavanje postojećih metoda fraktalne analize morfologije neurona i provera prognostičkog značaja monofraktalne i multifraktalne analize histopatoloških uzoraka tumora dojke. Predstavljene su modifikacije metoda brojanja kvadrata, metoda brojanja segmenata i kumulativnog metoda merenja mase. Modifikacijom metode brojanja kvadrata postignut je optimalniji zakon skaliranja i smanjen je uticaj promene rezolucije i rotacije objekta na vrednost fraktalne dimenzije. Modifikovanom metodom brojanja krugova preciznije se kvantifikuje nepravilnost dendrita. Modifikacijom kumulativnog metoda merenja mase izbegnut je problem višestruke vrednosti fraktalne dimenzije za isti objekat. Analizirane su morfološke razlike između neurona nukleusa kaudatusa i putamena (strijatuma čoveka) i između spoljašnjih i unutrašnjih graničnih neurona zupčastog jedra. Iz rezultata se zaključuje da metoda brojanja kvadrata ne razdvaja adekvatno grupe neurona. Statistički značajne razlike su primećene za parametre lakunarnosti i fraktalne dimenzije brojanja krugova u slučaju neurona zupčastog jedra. Monofraktalnom i multifraktalnom analizom histopatoloških uzoraka tumora dojke na binarnim slikama i slikama sive skale došlo se do zaključka da monofraktalna analiza slika sive skale daje najbolje prognostičke rezultate.The complexity and irregularity of objects encountered in medical research show the need for finding new and adequate ways of description and for improvement of existing methods. The use of these new methods is emphasized in better classification and understanding of the function of various physiological phenomena and tissues, as well as in the diagnosis and risk prognosis of some diseases. Fractal analysis proved to be a useful tool for this purpose. The main themes of this thesis are the modification and improvement of existing methods of fractal analysis of neuron morphology and the verification of the prognostic importance of monofractal and multifractal analysis of histopathological breast tumor samples. Modifications of the box-count method, segment count method, and cumulative mass method are presented. By modifying the box-counting method, better scaling law has been achieved and the effects of resolution change and rotation of the object on the value of the fractal dimension have been reduced. Modified segment counting method more precisely quantifies the irregularity of dendrites. Modification of the cumulative mass method avoided the problem of multiple values of fractal dimension for the same object. Morphological differences between the neurons of the caudate nucleus and putamen (human striatum) and between the external and internal boundary neurons of the dentate nucleus were analyzed. It is concluded from the results that box-counting method does not adequately separate the groups of neurons. Statistically significant differences were observed for the parameters of lacunarity and circle-count fractal dimension in the case of dentate nucleus neurons. Monofractal and multifractal analysis were performed on binary and grayscale images of histopathological breast tumor samples. It is concluded that monofractal analysis of grayscale images achieved the best prognostic results

Individual-Based Modeling and Nonlinear Analysis for Complex Systems with Application to Theoretical Ecology

One approach to understanding the behaviour of complex systems is individual-based modeling, which provides a bottom-up approach allowing for the consideration of the traits and behaviour of individual organisms. Ecosystem models aim to characterize the major dynamics of ecosystems, in order to synthesize the understanding of such systems and to allow predictions of their behaviour. Moreover, ecosystem simulations have the potential to help scientists address theoretical questions as well as helping with ecological resource management. Because in reality biologists do not have much data regarding variations in ecosystems over long periods of time, using the results of ecological computer simulation for making reasonable predictions can help biologists to better understand the long-term behaviour of ecosystems. Different versions of ecosystem simulations have been developed to investigate several questions in ecology such as how speciation proceeds in the absence of experimenter-defined functions. I have investigated some of these questions relying on complex interactions between the many individuals involved in the system, as well as long-term evolutionary patterns and processes such as speciation and macroevolution. Most scientists now believe that natural phenomena have to be looking as a chaotic system. In the past few years, chaos analysis techniques have gained increasing attention over a variety of applications. I have analyzed results of complex models to see whether chaotic behaviour can emerge, since any attempt to model a realistic system needs to have the capacity to generate patterns as complex as the ones that are observed in real systems. To further understand the complex behaviour of real systems, a new algorithm for long-term prediction of time series behaviour is also proposed based on chaos analysis. We evaluated the performance of our new method with respect to the prediction of the Dow-Jones industrial index time series, epileptic seizure and global temperature anomaly

Do retinal microvascular abnormalities shed light on the pathophysiology of lacunar stroke?

Background. Lacunar strokes account for 25% of all ischaemic stroke but the exact nature of the causative cerebral small vessel abnormality remains unknown. Pathological studies are technically difficult and brain imaging cannot adequately characterise the cerebral small vessels. The retinal blood vessels are of similar size and physiology to the cerebral small vessels and may act as a surrogate marker for these cerebral small vessels. We therefore investigated retinal microvascular abnormalities in lacunar stroke. Methods. We performed a systematic review of retinal microvascular abnormalities in lacunar stroke to clarify associations and identify where further research was required. We then established a cohort of patients presenting with lacunar stroke with cortical stroke controls to investigate differences in retinal microvascular abnormalities between stroke subtypes. All patients had MRI brain at presentation and digital retinal photography of both eyes. We investigated the prevalence of retinopathy (hard and soft exudates or haemorrhages/microaneurysms), focal arteriolar narrowing and arteriovenous nicking . We developed, validated and used novel semi-automated techniques for measuring retinal arteriolar and venular widths, retinal arteriolar geometry (branching co-efficients (change in arteriolar cross sectional area across a bifurcation) and branching angles) and fractal dimensions (reflecting branching complexity) of the vasculature. We also assessed MRI parameters in lacunar stroke. We used multivariable analysis to correct for baseline imbalances in vascular risk factors. Results. From the systematic review we demonstrated that retinal microvascular abnormalities are associated with incident and prevalent stroke but that in general, strokes were inadequately characterised and there were no data regarding retinal microvascular abnormalities in ischaemic stroke subtypes. We recruited 253 patients, 129 lacunar strokes and 124 cortical strokes, mean age 68 years. We found no difference in the prevalence of retinopathy, arteriovenous nicking, focal arteriolar narrowing or arteriolar widths between lacunar and cortical stroke subtypes. We found that venules were wider in lacunar stroke. We found no differences in arteriolar branching co-efficients or arteriolar branching angles between lacunar and cortical strokes but found that deep white matter white matter hyperintensities on MRI were associated with increased branching co-efficients and periventricular white matter hyperintensities associated with decreased branching co-efficients. We found that the fractal dimension of the vascular tree was decreased in lacunar stroke. Furthermore we found that enlarged perivascular spaces on MRI are associated with lacunar stroke and white matter disease. Conclusions. We have clearly demonstrated that retinal microvascular abnormalities differ between lacunar and cortical stroke suggesting that a distinct small vessel vasculopathy may cause lacunar stroke. We have also identified MR markers of lacunar stroke. These results suggest that venular disease (a hitherto underresearched area) may play a role in the pathophysiology of lacunar stroke. Retinal microvascular abnormalities can act as markers for cerebral small vessel disease. We plan collaborative analyses with colleagues who have performed similar studies to further assess retinal abnormalities in lacunar stroke

Optimization of computational analysis of morphology of malignant epithelial nests of breast tumors in order to improve disease prognosis

Napredak u preživljavanju i poboljšanju kvaliteta života pacijenata sa rakom dojke se može ostvariti personalizacijom terapije koja trenutno nije u punoj meri izvodljiva usled nedovoljne pouzdanosti prognostičkih pokazatelja. Ova teza je zato imala cilj da identifikuje izvore prognostičkih informacija i poboljša njihove prognostičke performanse na osnovu morfometrijskih osobina epitelnih malignih plaža, tj. malignih klastera u tumoru dojke i njihove ekspresije citokeratina. Obuhvaćeno je 102 pacijentkinje bez sistemske terapije koja bi uticala na pojavu metastaza. Analizirane su 532 slike histopatoloških preparata tumora bojenih koktelom AE1/AE3 pan-citokeratinskih antitela čime je omogućena vizualizacija epitelnih ćelija koje su kod karcinoma dojke najčešće maligno transformisane. Da bi se ispitao uticaj ekspresije citokeratina na prognostički učinak, izvršena je segmentacija slika na sedam nepreklapajućih opsega intenziteta piksela. Identifikaciji morfometrijskog profila (oblik, veličina, broj) malignih plaža sa najvećim prognostičkim značajem pristupilo se kombinacijom binarizacije slika sive skale sa šest pragova, pet filtera cirkularnosti i četiri filtera veličine. Tako je dobijeno 120 setova slika sa malignim plažama razdvojenim u odnosu na njihovu morfologiju. Prognostički učinak izračunatih parametara je utvrđen ROC analizom, a njihov značaj i nezavisnost su ispitani Cox regresionim modelom, koristeći pojavu udaljenih metastaza kao ishod bolesti. Značaj pojave metastaza je u tome što su metastaze, a ne primarni tumor, uzrok smrtnosti kod raka dojke. Rezultati su pokazali koncentraciju prognostičkog značaja u epitelnim malignim plažama sa povećanom cirkularnošću i manjom veličinom, koje eksprimiraju citokeratine u srednjem i niskom intenzitetu. Pri tome su plaže sa najboljim prognostičkim performansama (AUC = 0.82) identifikovane kao pojedinačne epitelne ćelije rasute po stromi tumora. Njihov broj je bio najefikasniji i nezavisan prognostički parametar. Izuzetan prognostički značaj ovih ćelija je baziran i na činjenici da se one mogu identifikovati, kvantifikovati i analizirati ne samo računarskom analizom već i vizuelnim mikroskopskim pregledom...Progress in the survival and life quality improvement of breast cancer patients could be achieved by personalized treatment, which is currently not fully achievable due to insufficient reliability of prognostic factors. This thesis aimed to identify sources of prognostic information and improve their prognostic performance based on the morphometric properties of epithelial malignant nests (i.e., malignant clusters) in breast tumor and their cytokeratin expression. 102 patients without systemic therapy that could affect the metastases occurrence were studied. 532 images of tumors tissue samples stained by the AE1/AE3 pan-cytokeratin antibody cocktail were analyzed, which enabled the visualization of epithelial cells that are most often malignantly transformed in breast cancer. To examine the effect of cytokeratin expression on prognostic efficiency, image segmentation was performed on seven non-overlapping pixel intensity ranges. The identification of the morphometric profile (shape, size, number) of malignant nests with the highest prognostic significance was accomplished applying six binarization thresholds in combination with five circularity filters and four size filters. Therefore, 120 sets of images were obtained with malignant nests separated based on their morphology. The prognostic performance of the extracted features was determined by ROC analysis, and their significance and independence were examined by Cox regression model, using distant metastasis occurrence as an endpoint event. The significance of metastasis occurrence is that metastasis, and not the primary tumor, is the cause of breast cancer mortality. The results showed that malignant epithelial nests with greater circularity, smaller size and with medium and low intensity of cytokeratin expression, are the most important for prognosis..