L. M. Brasil

Breast cancer image assessment using an adaptative network-based fuzzy inference system

In Brazil breast cancer is the foremost cause of fatality by cancer for women. Given that the causes are unidentified, it cannot be prevented. Mammography is one of the most reliable exams for breast cancer detection and it is based on image analysis by radiologists. Early detection is the key issue for breast cancer control and computer-aided diagnosis system can help ra diologists in detection and diagnosing breast abnormalities. Hybrid neuro-fuzzy systems are suitable for pattern recognition tasks and therefore useful for medical diagnosis support through pattern identification in mammographic images. This study presents an Adaptative Network-based Fuzzy Inference System (ANFIS) that classifies the mammographic images calcification region of interest as benign or malign and provides an important tool for breast cancer image assessment. The ANFIS model, utilized in the mammogram region of interest’s classification phase, reached a maximum accuracy rate of 99.75%.

Mensuração de área de úlceras por pressão por meio dos softwares Motic e do AutoCAD

A ulcera por pressao e uma lesao parcial ou total das camadas da pele em determinadas regioes do corpo e seu processo de cicatrizacao pode ser acompanhado por meio de processamento de imagens. A analise da area da ulcera por pressao e relevante para avaliacao da sua evolucao e de sua resposta a procedimentos terapeuticos. Os softwares Motic e AutoCAD® permitem avaliar a area de regioes de uma imagem atraves da marcacao do seu contorno. Valendo-se dessa tecnica, 35 voluntarios determinaram as areas de duas ulceras por pressao grau III pelos dois tipos de software. Concluiu-se que eles apresentam resultados clinicamente concordantes e podem assim ser utilizados para acompanhamento da evolucao da cicatrizacao de ulceras por pressao.Pressure ulcer is a lesion that affects skin layers in some regions of the body and its healing can be followed up using image processing. The analysis of pressure ulcer area is relevant to evaluate its evolution and response to therapeutic procedures. Such areas can be evaluated through contour marking with the softwares Motic and AutoCAD®. In this study 35 volunteers computed areas from two grade III pressure ulcers using these instruments. It was possible to conclude that results are clinically equivalent and so can be considered to follow up healing evolution from pressure ulcers.

Automatic counting of Aedes Aegypti eggs deposited in ovitrap by algorithm of Digital Image Processing and Artificial Neural Network

According to World Health Organization, Dengue is identified as one of the main pandemic viral disease in tropical and semi-tropical countries in the world. A lot of researches have divulged that the use of ovitraps has itself shown a simple and inexpensive alternative for monitoring and controlling Dengue vector, Aedes Aegypti, but generally the process of counting Dengue mosquito eggs in ovitraps is performed manually. This paper describes a proposal for automatic counting of Aedes Aegypti eggs deposited in ovitraps by Digital Image Processing techniques associated to an Artificial Neural Network.

Auxiliary System For Computer-Aided Evaluation of Breast Calcifications Based on Digital Image Processing and Artificial Neural Networks

Early diagnosis still represents the best approach in the prevention and control of breast cancer, the second most frequent form of cancer worldwide. In this context, mammography has been largely used as a major method for disease early detection, as it aids the early identification of calcification clusters that can be or can later become tumors. This paper discusses the use of Wavelet Transforms to help highlight calcification areas in combination with digital image morphological techniques for feature extraction from regions of interest in digital mammography. The results obtained in this work are being upgraded to a next step, which will use a MultiLayer Perceptron artificial neural network to classify calcifications according to the most applicable category in the Breast Imaging Reporting and Data System (BIRADS).

Morphological analysis for feature extraction and classification of breast calcifications

Calcifications (calcium build-ups) in breast regions are frequently found in breast screening examinations. It is estimated that 90% of nonpalpable intraductal breast cancers are detectable morphologically by the presence of calcifications. This work performs a morphological analysis of regions of interest related to breast calcifications by extraction of a set of features that help the health care provider in the automatic classification of these calcifications. The results are being validated in a controlled test that simulates calcifications in order to consider morphological information that characterizes the geometrical characteristics. This allows one to assign an object signature and hence to approximate the test conditions to real calcifications.

Artificial Neural Network Interactive Activation and Competition Model Service-Oriented Applied to Health

This paper presents the steps towards the construction of a model for the Artificial Neural Network (ANN) of the Interactive Activation and Competition (IAC) type and under the paradigms of a Service-Oriented Architecture (SOA). Also, as a case study, recovering the content related to Female Breast Anatomy as the first register of an ANN IAC Service-Oriented. On its stages three models for ANN execution are presented and compared on its execution and performance. This paper contributes for an ANN IAC Service- Oriented model definition as well as the performance of a teaching role on the healthcare areas, strengthening the research and the new technologies development, mainly in the adaptive interface areas and intelligent tutoring systems.

An approach to provide visual information to support skin wounds therapy

Availability of visual information means an effective way to improve specialized work in quite different areas. They enable reality modeling, a faster context analysis, a more successful search for problem solutions, an objective oriented decision making, as well as important elements for instructional processes. Avisual model is a simulation form that stimulate insights, say, creative answers to yet open questions and derivation of yet not imagined possible facts concerning a studied reality. Visual features of human body are highly relevant as basic information for a variety of decisions on activities in health domain. Through mechanisms of user-friendly interface one can promptly access and eventually perform adjustments. One can achieve better life quality and greater efficiency in health service from state as well. This paper describes an approach towards a visualization process of skin lesions, including features recognition for therapeutic processes and relevant decisions, with experimental validation.

Using Computer Games as a Strategy for Maintaining the Cognitive Capacity of the Elderly

The Promoting Cognitive Performance - ProDC system was created for serving like an instrument for therapeutic intervention by health professionals working with cognitive rehabilitation. The ProDC seeks to train cognitive functions by means of computer games with graded levels of difficulty. The target audiences are the elderly aged 60 or more who have a deficit cognitive impairment diagnosis. So, nine games have been implemented for therapeutic intervention. The ProDC is being evaluated in the Institution Long-Permanence in Distrito Federal, Brazil.

Computer games with therapeutic potential for maintaining cognitive abilities of elderly people

The use computer games in cognitive rehabilitation programs is a new trend by health professionals. In this perspective, nine computer games were developed for cognitive stimulation of the elderly people with cognitive deficit.

Envisioning Ecosystems - Biodiversity, Infirmity and Affectivity

Earth’s biosphere, climate biodiversity crises and environmental issues are raising a profound level of awareness concerning the collective responsibility toward Earth’s life and demanding the responsibility for promoting a healthy ecosystem. A new transdisciplinar group of Brazilian researchers at the University of Brasilia at Gama (FGA), working on the Biomedical Engineering Graduate Program, shares with the international community of Art and TechnoScience several themes related to the ecosystem biodiversity and the extremophile condition (Bec, 2007). We consider our responsibility and the urgent attention to life in our country’s huge territory, while facing the effects of an endemic infection of tropical climates and working for the preservation of the Biomes in Amazon Forest, the lung of the planet. Our collaborative projects are concerned with infirmity of the territory and the human invasion and destruction of the ecosystem self-organizing defence. Consequently, we work on health care and affective geographies, in the sense postulated by the geographer/philosopher Milton Santos (Santos, 2008 & Santos, 2009) renewed by geolocated and ubiquitous condition and sentient technologies. Interventions in social networks allow people to exist in the sense of being here and there, consisting of a largely sense of place, to be co-located, being connected everywhere, with an awareness of place amplified by the power to take care of the ecosystem. Our project leads with landscapes as a living organism in a given geography, being socially engineered, from the conceptual subjective use of space to the advanced mobile telematic computing and ubiquitous data processing and data information visualization by applying the perspective of acting everywhere – and specially in extreme and hostile space.