Questing one Brazilian query: reporting 16 cases of Q fever from Minas Gerais, Brazil

Q fever has been considered non-existing in Brazil where reports of clinical cases still cannot be found. This case-series of 16 patients is a result of a systematic search for such illness by means of clinical and serologic criteria. Serologic testing was performed by the indirect microimmunofluorescence technique using phase I/II C. burnetii antigens. Influenza-like syndrome was the most frequent clinical form (eight cases - 50%), followed by pneumonia, FUO (fever of unknown origin), mono-like syndrome (two cases - 12.5% each), lymphadenitis (one case - 6.3%) and spondylodiscitis associated with osteomyelitis (one case - 6.3%). The ages varied from four to 67 years old with a median of 43.5. All but one patient had positive serologic tests for phase II IgG whether or not associated with IgM positivity compatible with acute infection. One patient had both phase I and phase II IgG antibodies compatible with chronic Q fever. Seroconvertion was detected in 10 patients. Despite the known limitations of serologic diagnosis, the cases here reported should encourage Brazilian doctors to include Q fever as an indigenous cause of febrile illness.

Regards croisés francophones et portugais : les images des Portugais dans la littérature romanesque contemporaine (1950-2000)

Tese de doutoramento em Línguas e Literaturas Românicas, Literatura Românica Comparada

A qualitive reasoning approach for improving query results for sketch based queries by topological analysis of spatial aggregation

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

Distributed processing of large remote sensing images using MapReduce - A case of Edge Detection

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

Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Unsupervised classification of remote sensing images combining Self Organizing Maps and segmentation techniques

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

Extracting temporal and spatial distributions information about marine mucilage phenomenon based on Modis satellite images; a case study of the Tyrrhenian and the Adriatic Sea, 2010-2012

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

Expressiveness improvements of OutSystems DSL query primitives

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Sensitivity correction of images obtained with the prototype Clear-PEM in pre-clinical environment

Dissertation presented at Faculdade de Ciências e Tecnologia Universidade Nova de Lisboa to obtain a Master Degree in Biomedical Engineering

Calibration, selection and mosaicing of SMART-1 AMIE images

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Interactive acquisition of spatial information from images for multimedia applications

Dissertação para obtenção do Grau de Doutor em Informática

Characterization and surface reconstruction of objects in tomographic images of composite materials

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Automatic delimitation of the clinical region of interest in ultra-wide field of view images of the retina

Retinal ultra-wide field of view images (fundus images) provides the visu-alization of a large part of the retina though, artifacts may appear in those images. Eyelashes and eyelids often cover the clinical region of interest and worse, eye-lashes can be mistaken with arteries and/or veins when those images are put through automatic diagnosis or segmentation software creating, in those cases, the appearance of false positives results. Correcting this problem, the first step in the development of qualified auto-matic diseases diagnosis programs can be done and in that way the development of an objective tool to assess diseases eradicating the human error from those processes can also be achieved. In this work the development of a tool that automatically delimitates the clinical region of interest is proposed by retrieving features from the images that will be analyzed by an automatic classifier. This automatic classifier will evaluate the information and will decide which part of the image is of interest and which part contains artifacts. The results were validated by implementing a software in C# language and validated through a statistical analysis. From those results it was confirmed that the methodology presented is capable of detecting artifacts and selecting the clin-ical region of interest in fundus images of the retina.