Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

Chapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedings

Modelling and segmentation of the vocal tract during speech production by using deformable models in magnetic resonance images

The first and second authors would like to thank the support of the PhD grants with references SFRH/BD/28817/2006 and SFRH/PROTEC/49517/2009, respectively, from Fundação para a Ciência e Tecnol ogia (FCT). This work was partially done in the scope of the project “Methodologies to Analyze Organs from Complex Medical Images – Applications to Fema le Pelvic Cavity”, wi th reference PTDC/EEA- CRO/103320/2008, financially supported by FCT.

Damage analysis of carbon/epoxy plates after drilling

Drilling of composites plates normally uses traditional techniques but damage risk is high. NDT use is important. Damage in a carbon/epoxy plate is evaluated by enhanced X-rays. Four different drills are used. The images are analysed using Computational Vision techniques. Surface roughness is compared. Results suggest strategies for delamination reduction.

Imagiologia Espetral - Análise Forense de Notas e Escrita Manual

A análise forense de documentos é uma das áreas das Ciências Forenses, responsável pela verificação da autenticidade dos documentos. Os documentos podem ser de diferentes tipos, sendo a moeda ou escrita manual as evidências forenses que mais frequentemente motivam a análise. A associação de novas tecnologias a este processo de análise permite uma melhor avaliação dessas evidências, tornando o processo mais célere. Esta tese baseia-se na análise forense de dois tipos de documentos - notas de euro e formulários preenchidos por escrita manual. Neste trabalho pretendeu-se desenvolver técnicas de processamento e análise de imagens de evidências dos tipos referidos com vista a extração de medidas que permitam aferir da autenticidade dos mesmos. A aquisição das imagens das notas foi realizada por imagiologia espetral, tendo-se definidas quatro modalidades de aquisição: luz visível transmitida, luz visível refletida, ultravioleta A e ultravioleta C. Para cada uma destas modalidades de aquisição, foram também definidos 2 protocolos: frente e verso. A aquisição das imagens dos documentos escritos manualmente efetuou-se através da digitalização dos mesmos com recurso a um digitalizador automático de um aparelho multifunções. Para as imagens das notas desenvolveram-se vários algoritmos de processamento e análise de imagem, específicos para este tipo de evidências. Esses algoritmos permitem a segmentação da região de interesse da imagem, a segmentação das sub-regiões que contém as marcas de segurança a avaliar bem como da extração de algumas características. Relativamente as imagens dos documentos escritos manualmente, foram também desenvolvidos algoritmos de segmentação que permitem obter todas as sub-regiões de interesse dos formulários, de forma a serem analisados os vários elementos. Neste tipo de evidências, desenvolveu-se ainda um algoritmo de análise para os elementos correspondentes à escrita de uma sequência numérica o qual permite a obtenção das imagens correspondentes aos caracteres individuais. O trabalho desenvolvido e os resultados obtidos permitiram a definição de protocolos de aquisição de imagens destes tipos de evidências. Os algoritmos automáticos de segmentação e análise desenvolvidos ao longo deste trabalho podem ser auxiliares preciosos no processo de análise da autenticidade dos documentos, o qual, ate então, é feito manualmente. Apresentam-se ainda os resultados dos estudos feitos às diversas evidências, nomeadamente as performances dos diversos algoritmos analisados, bem como algumas das adversidades encontradas durante o processo. Apresenta-se também uma discussão da metodologia adotada e dos resultados, bem como de propostas de continuação deste trabalho, nomeadamente, a extração de características e a implementação de classificadores capazes aferir da autenticidade dos documentos.

High-Content Analysis of Breast Cancer Using Single-Cell Deep Transfer Learning

High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.

Detecção e Quantificação de Neurónios em C.elegans

Nesta dissertação é apresentado um estudo dos sistemas de processamento automático de imagem em contexto de um problema relacionado com a individualização de neurónios em imagens da nematoda C. elegans durante estudos relacionados com a doença de Parkinson. Apresenta-se uma breve introdução à anatomia do verme, uma introdução à doença de Parkinson e uso do C. elegans em estudos relacionados e também é feita a análise de artigos em contexto de processamento de imagem para contextualizar a situação atual de soluções para o problema de extração de características e regiões específicas. Neste projeto é desenvolvida uma pipeline com o auxilio do software CellProfiler para procurar uma resposta para o problema em questão.

Urban sprawl analysis and modeling in Asmara, Eritreia: Application of Geospatial Tools

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

Pore space analysis of beech wood: The vessel network

Water transport in wood is vital for the survival of trees. With synchrotron radiation X-ray tomographic microscopy (SRXTM), it has become possible to characterize and quantify the three-dimensional (3D) network formed by vessels that are responsible for longitudinal transport. In the present study, the spatial size dependence of vessels and the organization inside single growth rings in terms of vessel-induced porosity was studied by SRXTM. Network characteristics, such as connectivity, were deduced by digital image analysis from the processed tomographic data and related to known complex network topologies.

Morphometric Analysis of McCoy Cells Inoculated with Cerebrospinal Fluid from Patients with Rabies

To demonstrate the potential of McCoy cells for the isolation of rabies virus from the cerebrospinal (CSF) fluid of a patient with a diagnosis of rabies, McCoy cells were inoculated with CSF from a patient with a clinical diagnosis of rabies and investigated in terms of morphometric aspect using the JAVA analysis system for the quantification of the increased size of infected cells compared to noninfected cells. The cells were also examined in terms of specific staining for the diagnosis of rabies by the method of Sellers for the observation of intracytoplasmic inclusions and by specific immunofluorescence staining for rabies virus. Infected cells showed changes in cell permeability and morphologic modifications which differed significantly compared to normal cells (P<0.001) when analyzed by the Mann-Whitney and Kruskal-Wallis tests. Intense activity of the endoplasmic reticulum was also observed, as indicated by the presence of intracytoplasmic inclusions visualized by specific staining. The present study demonstrated the isolation of rabies virus from the CSF of a patient with rabies, showing that McCoy cells can be used for the laboratory diagnosis of patients suspected to have rabies.

Morphologic and morphometric analysis of Hepatozoon spp. (Apicomplexa, Hepatozoidae) of snakes

Hepatozoon species are the most abundant hemoparasites of snakes. Its identification has been based mainly on the morphologic characterization of the gamonts in the peripheral blood of the vertebrate host and also of the cysts found in the internal organs of the vertebrate and invertebrate hosts. Using a computerized image analysis system, we studied five species of Hepatozoon from recently captured snakes in Botucatu, State of São Paulo, Brazil, to evaluate the importance of the morphology and morphometry of the gamonts for the characterization of Hepatozoon species and to analyze the morphologic changes induced in the erythrocytes by the parasite. The studied species were H. terzii of Boa constrictor amarali, Hepatozoon sp. of Crotalus durissusterrificus, H. philodryasi of Philodryas patagoniensis, and H. migonei and H. cyclagrasi of Hydrodynastes gigas. We observed three different groups, one of them including the species H. terzii, H. philodryasi and Hepatozoon sp. of C. durissus terrificus; and the other two consisting of H. migonei and H. cyclagrasi. Degree of alterations in the erythrocytes was variable and it may be useful for characterization of Hepatozoon species.

Compression-based Image Registration

Image registration is an important component of image analysis used to align two or more images. In this paper, we present a new framework for image registration based on compression. The basic idea underlying our approach is the conjecture that two images are correctly registered when we can maximally compress one image given the information in the other. The contribution of this paper is twofold. First, we show that the image registration process can be dealt with from the perspective of a compression problem. Second, we demonstrate that the similarity metric, introduced by Li et al., performs well in image registration. Two different versions of the similarity metric have been used: the Kolmogorov version, computed using standard real-world compressors, and the Shannon version, calculated from an estimation of the entropy rate of the images

Sexual dimorphism of the human mandible: demonstration by elliptical Fourier analysis.

A new quantitative approach of the mandibular sexual dimorphism, based on computer-aided image analysis and elliptical Fourier analysis of the mandibular outline in lateral view is presented. This method was applied to a series of 117 dentulous mandibles from 69 male and 48 female individuals native of Rhenish countries. Statistical discriminant analysis of the elliptical Fourier harmonics allowed the demonstration of a significant sexual dimorphism in 97.1% of males and 91.7% of females, i.e. in a higher proportion than in previous studies using classical metrical approaches. This original method opens interesting perspectives for increasing the accuracy of sex identification in current anthropological practice and in forensic procedures.

Deoxyribonucleic acid content as an indicator of progression of squamous cell carcinogenesis in the esophagus: comparative analysis on imprint-cytospin and tissue section preparation.

BACKGROUND: The purpose of this study was to explore the potential use of image analysis on tissue sections preparation as a predictive marker of early malignant changes during squamous cell (SC) carcinogenesis in the esophagus. Results of DNA ploidy quantification on formalin-fixed, paraffin-embedded tissue using two different techniques were compared: imprint-cytospin and 6 microm thick tissue sections preparation. METHODS: This retrospective study included 26 surgical specimens of squamous cell carcinoma (SCC) from patients who underwent surgery alone at the Department of Surgery in CHUV Hospital in Lausanne between January 1993 and December 2000. We analyzed 53 samples of healthy tissue, 43 tumors and 7 lymph node metastases. RESULTS: Diploid DNA histogram patterns were observed in all histologically healthy tissues, either distant or proximal to the lesion. Aneuploidy was observed in 34 (79%) of 43 carcinomas, namely 24 (75%) of 32 early squamous cell carcinomas and 10 (91%) of 11 advanced carcinomas. DNA content was similar in the different tumor stages, whether patients presented with single or multiple synchronous tumors. All lymph node metastases had similar DNA content as their primary tumor. CONCLUSIONS: Early malignant changes in the esophagus are associated with alteration in DNA content, and aneuploidy tends to correlate with progression of invasive SCC. A very good correlation between imprint-cytospin and tissue section analysis was observed. Although each method used here showed advantages and disadvantages; tissue sections preparation provided useful information on aberrant cell-cycle regulation and helped select the optimal treatment for the individual patient along with consideration of other clinical parameters.

On the convergence of EM-like algorithms for image segmentation using Markov random fields.

Inference of Markov random field images segmentation models is usually performed using iterative methods which adapt the well-known expectation-maximization (EM) algorithm for independent mixture models. However, some of these adaptations are ad hoc and may turn out numerically unstable. In this paper, we review three EM-like variants for Markov random field segmentation and compare their convergence properties both at the theoretical and practical levels. We specifically advocate a numerical scheme involving asynchronous voxel updating, for which general convergence results can be established. Our experiments on brain tissue classification in magnetic resonance images provide evidence that this algorithm may achieve significantly faster convergence than its competitors while yielding at least as good segmentation results.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.