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DC Field | Value | Language |
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dc.contributor.author | Carvalho, Elizabeth, Simão | - |
dc.date.accessioned | 2012-01-17T15:11:30Z | - |
dc.date.available | 2012-01-17T15:11:30Z | - |
dc.date.issued | 2008 | - |
dc.identifier.uri | http://hdl.handle.net/10884/293 | - |
dc.description.abstract | Visualization is the realistic or abstract visual representation of a dataset that is generated by computer models or resulting from physical measurements of the real world. Visualization is fundamental to help people understand data and complexes processes and can be categorized according its goals (scientific or information). The correct data model and characterization are essential to the right choice of the visualization techniques and the production of useful visualizations. The great challenge lies in how to determine that the results are showed to the final users at the same time in a coherent, useful and simple way. The cartographic model concept was developed by Dana Tomlin in 1983 with the Map Analysis Package2 [Sendra2000]. A cartographic model can be seen as a collection of maps that are registered in a cartographic database, where each map is a “variable” that can be mathematically operated. These operations may involve primitives such as points or areas of different maps, for example, in a sequential order to interpret and solve spatial problems. In this context, the sequence of operations is similar to the algebraic solution of a group of equations. The creation of automatic tools for human’s body data analysis and visualization is a field in expansion and of great interest. However these tools are very valuable, they suffer from a common limitation that is imposed by their basis architectural model. In general, they rarely represent in a suitable way biological, morphological and/or biomedical data spatial interdependency. These models treat data in an almost total focused and independent way. The human body systems and organs work as a complex machine, where each part depends strongly on the others. This dependency might be stronger or weaker to the system or organ importance on the overall patient condition. The doctor diagnoses an illness by comparing and analyzing information not only directly related to the mostly affected organ, but also to the body as a whole. In fact the doctor performs a subtle spatial analysis, and therefore, executes a typical algebraic map operation in his/her mind, when diagnosing a patient. An illness might arouse different symptoms and physiological changes in systems/organs that are not directly related to the spatial location of it. CHUB is a model that was developed taking into consideration the main principles of cartographic modelling. It structures data according to different layers of information. Each layer is associated to a specific organ and/or system, and might contain geometric data or attributes that are “human-referenced”. CHUB has not been developed as a dynamic model. It is considered that dynamic issues related to human’s body data, such as body movement, blood flow or heartbeat (besides others) will be accomplished by other models that should be used as a specialized extension to CHUB. In order to validate CHUB two cases of study were considered – osteoarthritis knee diagnosis and hydrokinetic therapy sessions analysis, proposed two strategies for its validation and a prototype implemented. This prototype allowed its utilization, evaluation and validation in two different domains. The results achieved after its utilization and test lead to a complete CHUB validation. | pt_PT |
dc.language.iso | por | - |
dc.publisher | Universidade do Minho | pt_PT |
dc.rights | openAccess | en |
dc.subject | Computação gráfica | pt_PT |
dc.subject | visualização científica | pt_PT |
dc.subject | modelação cartográfica | pt_PT |
dc.subject | artrose | pt_PT |
dc.title | CHUB : um modelo cartográfico para a visualização e análise do corpo humano | pt_PT |
dc.type | doctoralThesis | pt_PT |
Appears in Collections: | A CTIC/STI - Teses de Doutoramento |
Files in This Item:
File | Description | Size | Format | |
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TeseDoutorado2008.pdf | 9.39 MB | Adobe PDF | View/Open |
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