967 resultados para Digital Image Analysis
Resumo:
This master’s thesis describes the research done at the Medical Technology Laboratory (LTM) of the Rizzoli Orthopedic Institute (IOR, Bologna, Italy), which focused on the characterization of the elastic properties of the trabecular bone tissue, starting from october 2012 to present. The approach uses computed microtomography to characterize the architecture of trabecular bone specimens. With the information obtained from the scanner, specimen-specific models of trabecular bone are generated for the solution with the Finite Element Method (FEM). Along with the FEM modelling, mechanical tests are performed over the same reconstructed bone portions. From the linear-elastic stage of mechanical tests presented by experimental results, it is possible to estimate the mechanical properties of the trabecular bone tissue. After a brief introduction on the biomechanics of the trabecular bone (chapter 1) and on the characterization of the mechanics of its tissue using FEM models (chapter 2), the reliability analysis of an experimental procedure is explained (chapter 3), based on the high-scalable numerical solver ParFE. In chapter 4, the sensitivity analyses on two different parameters for micro-FEM model’s reconstruction are presented. Once the reliability of the modeling strategy has been shown, a recent layout for experimental test, developed in LTM, is presented (chapter 5). Moreover, the results of the application of the new layout are discussed, with a stress on the difficulties connected to it and observed during the tests. Finally, a prototype experimental layout for the measure of deformations in trabecular bone specimens is presented (chapter 6). This procedure is based on the Digital Image Correlation method and is currently under development in LTM.
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Der Tumorstoffwechsel ist charakterisiert durch eine erhöhte Glykolyserate und die Anreicherung von Laktat auch in Anwesenheit von Sauerstoff. In früheren Arbeiten dieser Arbeitsgruppe konnte gezeigt werden, dass ein hoher Laktatgehalt in Primärtumoren signifikant mit einem gesteigerten Metastasierungsverhalten und einer schlechteren Patientenprognose verknüpft ist. Ein wichtiges Verfahren zur Bestimmung des Metabolitstatus in kryokonservierten Tumorschnitten ist die induzierte, metabolische Biolumineszenz. Im Rahmen dieser Arbeit wurde ein neues, digitales Kamerasystem für Biolumineszenzmessungen etabliert. Außerdem wurde der für die Laktat- und Glukosemessungen benötigte Enzymmix optimiert, so dass eine bessere Lichtausbeute und eine Kosteneinsparung von etwa 50% erzielt werden konnte. Durch die Einführung von Kontrollmessungen und die Verwendung eines neu entwickelten ImageJ-PlugIns für eine halbautomatisierte Auswertung, konnte ein zuverlässiges Messsystem etabliert werden, das Ergebnisse mit einer verbesserten Reproduzierbarkeit liefert. rnDieses neue Messsytem wurde in einer Studie an zehn humanen xenotransplantierten Plattenepithelkarzinomen des Kopf-Hals-Bereiches erfolgreich eingesetzt. Es konnte gezeigt werden, dass eine signifikante, positive Korrelation zwischen dem Laktatgehalt in soliden Primärtumoren und der Resistenz gegenüber einer fraktionierten Strahlentherapie besteht. rnIn einer weiterführenden Studie wurde im gleichen Xenograftmodell der Einfluss einer fraktionierten Strahlentherapie auf den Tumorstoffwechsel untersucht. Der Vergleich von zwei humanen Plattenepithelkarzinomlinien des Kopf-Hals-Bereichs im Verlauf einer fraktionierten Strahlentherapie zeigt deutliche Unterschiede zwischen strahlenresistenten und strahlensensiblen Tumoren. In der strahlenempfindlichen Tumorlinie UT-SCC 14 treten nach Bestrahlung mit drei Fraktionen in der Expression glykolyse-assoziierter Gene und nach zehn Fraktionen im ATP- und Laktatgehalt signifikante Veränderungen auf. Im Gegensatz dazu wird bei der strahlenresistenten Linie UT-SCC 5 lediglich eine Absenkung des Laktatgehaltes nach zehn Fraktionen beobachtet, nicht jedoch des ATP-Gehalts. Die mRNA-Expression wird in UT-SCC 5 nicht durch eine fraktionierte Bestrahlung verändert. Diese Ergebnisse liefern erste Hinweise, dass das mRNA-Expressionslevel und der Metabolitgehalt frühe Marker für das Ansprechen auf eine Strahlentherapie sein können.rn
Resumo:
Fino dagli albori della metodica scientifica, l’osservazione e la vista hanno giocato un ruolo fondamentale. La patologia è una scienza visiva, dove le forme, i colori, le interfacce e le architetture di organi, tessuti, cellule e componenti cellulari guidano l’occhio del patologo e ne indirizzano la scelta diagnostico-classificativa. L’osservazione del preparato istologico in microscopia ottica si attua mediante l’esame e la caratterizzazione di anomalie ad ingrandimenti progressivamente crescenti, a diverse scale spaziali, che partono dalla valutazione dell’assetto architettonico sovracellulare, per poi spostarsi ad investigare e descrivere le cellule e le peculiarità citomorfologiche delle stesse. A differenza di altri esami di laboratorio che sono pienamente quantificabili, l’analisi istologica è intrinsecamente soggettiva, e quindi incline ad un alto grado di variabilità nei risultati prodotti da differenti patologi. L’analisi d’immagine, l’estrazione da un’immagine digitale di contenuti utili, rappresenta una metodica oggettiva, valida e robusta ormai largamente impiegata a completamento del lavoro del patologo. Si sottolinea come l’analisi d’immagine possa essere vista come fase descrittiva quantitativa di preparati macroscopici e microscopici che poi viene seguita da una interpretazione. Nuovamente si sottolinea come questi descrittori siano oggettivi, ripetibili e riproducibili, e non soggetti a bassa concordanza inter operatore. La presente tesi si snoda attraverso un percorso concettuale orientato ad applicazioni di analisi d’immagine e patologia quantitativa che parte dalle applicazioni più elementari (densità, misure lineari), per arrivare a nozioni più avanzate, quali lo studio di complessità delle forme mediante l’analisi frattale e la quantificazione del pattern spaziale di strutture sovracellulari.
Resumo:
A laser scanning microscope collects information from a thin, focal plane and ignores out of focus information. During the past few years it has become the standard imaging method to characterise cellular morphology and structures in static as well as in living samples. Laser scanning microscopy combined with digital image restoration is an excellent tool for analysing the cellular cytoarchitecture, expression of specific proteins and interactions of various cell types, thus defining valid criteria for the optimisation of cell culture models. We have used this tool to establish and evaluate a three dimensional model of the human epithelial airway wall.
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Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.
Resumo:
Non-linear image registration is an important tool in many areas of image analysis. For instance, in morphometric studies of a population of brains, free-form deformations between images are analyzed to describe the structural anatomical variability. Such a simple deformation model is justified by the absence of an easy expressible prior about the shape changes. Applying the same algorithms used in brain imaging to orthopedic images might not be optimal due to the difference in the underlying prior on the inter-subject deformations. In particular, using an un-informed deformation prior often leads to local minima far from the expected solution. To improve robustness and promote anatomically meaningful deformations, we propose a locally affine and geometry-aware registration algorithm that automatically adapts to the data. We build upon the log-domain demons algorithm and introduce a new type of OBBTree-based regularization in the registration with a natural multiscale structure. The regularization model is composed of a hierarchy of locally affine transformations via their logarithms. Experiments on mandibles show improved accuracy and robustness when used to initialize the demons, and even similar performance by direct comparison to the demons, with a significantly lower degree of freedom. This closes the gap between polyaffine and non-rigid registration and opens new ways to statistically analyze the registration results.
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A novel microfluidic method is proposed for studying diffusion of small molecules in a hydrogel. Microfluidic devices were prepared with semi-permeable microchannels defined by crosslinked poly(ethylene glycol) (PEG). Uptake of dye molecules from aqueous solutions flowing through the microchannels was observedoptically and diffusion of the dye into the hydrogel was quantified. To complement the diffusion measurements from the microfluidic studies, nuclear magnetic resonance(NMR) characterization of the diffusion of dye in the PEG hydrogels was performed. The diffusion of small molecules in a hydrogel is relevant to applications such asdrug delivery and modeling transport for tissue-engineering applications. The diffusion of small molecules in a hydrogel is dependent on the extent of crosslinking within the gel, gel structure, and interactions between the diffusive species and the hydrogel network. These effects were studied in a model environment (semi-infinite slab) at the hydrogelfluid boundary in a microfluidic device. The microfluidic devices containing PEG microchannels were fabricated using photolithography. The unsteady diffusion of small molecules (dyes) within the microfluidic device was monitored and recorded using a digital microscope. The information was analyzed with techniques drawn from digital microscopy and image analysis to obtain concentration profiles with time. Using a diffusion model to fit this concentration vs. position data, a diffusion coefficient was obtained. This diffusion coefficient was compared to those from complementary NMR analysis. A pulsed field gradient (PFG) method was used to investigate and quantify small molecule diffusion in gradient (PFG) method was used to investigate and quantify small molecule diffusion in hydrogels. There is good agreement between the diffusion coefficients obtained from the microfluidic methods and those found from the NMR studies. The microfluidic approachused in this research enables the study of diffusion at length scales that approach those of vasculature, facilitating models for studying drug elution from hydrogels in blood-contacting applications.
Resumo:
The study describes brain areas involved in medial temporal lobe (mTL) seizures of 12 patients. All patients showed so-called oro-alimentary behavior within the first 20 s of clinical seizure manifestation characteristic of mTL seizures. Single photon emission computed tomography (SPECT) images of regional cerebral blood flow (rCBF) were acquired from the patients in ictal and interictal phases and from normal volunteers. Image analysis employed categorical comparisons with statistical parametric mapping and principal component analysis (PCA) to assess functional connectivity. PCA supplemented the findings of the categorical analysis by decomposing the covariance matrix containing images of patients and healthy subjects into distinct component images of independent variance, including areas not identified by the categorical analysis. Two principal components (PCs) discriminated the subject groups: patients with right or left mTL seizures and normal volunteers, indicating distinct neuronal networks implicated by the seizure. Both PCs were correlated with seizure duration, one positively and the other negatively, confirming their physiological significance. The independence of the two PCs yielded a clear clustering of subject groups. The local pattern within the temporal lobe describes critical relay nodes which are the counterpart of oro-alimentary behavior: (1) right mesial temporal zone and ipsilateral anterior insula in right mTL seizures, and (2) temporal poles on both sides that are densely interconnected by the anterior commissure. Regions remote from the temporal lobe may be related to seizure propagation and include positively and negatively loaded areas. These patterns, the covarying areas of the temporal pole and occipito-basal visual association cortices, for example, are related to known anatomic paths.
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This article gives an overview over the methods used in the low--level analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of nucleic acid abundance in a set of tissues or cell populations for thousands of transcripts or loci simultaneously. Careful statistical design and analysis are essential to improve the efficiency and reliability of microarray experiments throughout the data acquisition and analysis process. This includes the design of probes, the experimental design, the image analysis of microarray scanned images, the normalization of fluorescence intensities, the assessment of the quality of microarray data and incorporation of quality information in subsequent analyses, the combination of information across arrays and across sets of experiments, the discovery and recognition of patterns in expression at the single gene and multiple gene levels, and the assessment of significance of these findings, considering the fact that there is a lot of noise and thus random features in the data. For all of these components, access to a flexible and efficient statistical computing environment is an essential aspect.
Resumo:
PURPOSE: To quantify optical coherence tomography (OCT) images of the central retina in patients with blue-cone monochromatism (BCM) and achromatopsia (ACH) compared with healthy control individuals. METHODS: The study included 15 patients with ACH, 6 with BCM, and 20 control subjects. Diagnosis of BCM and ACH was established by visual acuity testing, morphologic examination, color vision testing, and Ganzfeld ERG recording. OCT images were acquired with the Stratus OCT 3 (Carl Zeiss Meditec AG, Oberkochen, Germany). Foveal OCT images were analyzed by calculating longitudinal reflectivity profiles (LRPs) from scan lines. Profiles were analyzed quantitatively to determine foveal thickness and distances between reflectivity layers. RESULTS: Patients with ACH and BCM had a mean visual acuity of 20/200 and 20/60, respectively. Color vision testing results were characteristic of the diseases. The LRPs of control subjects yielded four peaks (P1-P4), presumably representing the RPE (P1), the ovoid region of the photoreceptors (P2), the external limiting membrane (ELM) (P3), and the internal limiting membrane (P4). In patients with ACH, P2 was absent, but foveal thickness (P1-P4) did not differ significantly from that in the control subjects (187 +/- 20 vs. 192 +/- 14 microm, respectively). The distance from P1 to P3 did not differ significantly (78 +/- 10 vs. 82 +/- 5 microm) between ACH and controls subjects. In patients with BCM, P3 was lacking, and P2 advanced toward P1 compared with the control subjects (32 +/- 6 vs. 48 +/- 4 microm). Foveal thickness (153 +/- 16 microm) was significantly reduced compared with that in control subjects and patients with ACH. CONCLUSIONS: Quantitative OCT image analysis reveals distinct patterns for controls subjects and patients with ACH and BCM, respectively. Quantitative analysis of OCT imaging can be useful in differentiating retinal diseases affecting photoreceptors. Foveal thickness is similar in both normal subjects and patients with ACH but is decreased in patients with BCM.
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PURPOSE: A microangiographical technique is described, which allows visualization of small and capillary blood vessels and quantification of fasciocutaneous blood vessels by means of digital computer analysis in very small laboratory animals. MATERIALS AND METHODS: The left carotid artery of 20 nu/nu mice was cannulated (26 gauge) and a mixture of gelatin, bariumsulfate, and green ink was injected according to standardized protocol. Fasciocutaneous blood vessels were visualized by digital mammography and analyzed for vessel length and vessel surface area as standardized units [SU] by computer program. RESULTS: With the described microangiography method, fasciocutaneous blood vessels down to capillary size level can be clearly visualized. Regions of interest (ROIs) can be defined and the containing vascular network quantified. Comparable results may be obtained by calculating the microvascular area index (MAI) and the microvascular length index (MLI), related to the ROIs size. Identical ROIs showed a high reproducibility for measured [SU] < 0.01 +/- 0.0012%. CONCLUSION: Combining microsurgical techniques, pharmacological knowledge, and modern digital image technology, we were able to visualize small and capillary blood vessels even in small laboratory animals. By using our own computer analytical program, quantification of vessels was reliable, highly reproducible, and fast.
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Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.