
Applying Image Mining to Support Gestational Age Determination
Please use this identifier to cite or link to this publication: http://hdl.handle.net/1926/217 |
Published in The Insight Journal - 2006 MICCAI Open Science Workshop.
Submitted by Luciano Silva on 07-08-2006.
The gestational age (GA) determination is one of the most used measures to guide diagnostics of specialists in neonatology to
guarantee the newborn surveillance. However, the currently available methods have been subject to a number of evaluations and criticism by important medical publications concerning both their low precision and their invasive procedures. Based on this scenario, the FootScanAge method was conceived, seeking to determine the GA through digital imaging of the newborn plantar surface. To support the evaluation and evolution of this new method, it was developed an Open Source and Java based Decision Support System that combines Data Mining and Image Processing techniques to implement the FootScanAge method. The system was developed taking advantage of high degree of interaction between experts in neonatology and computer science.
guarantee the newborn surveillance. However, the currently available methods have been subject to a number of evaluations and criticism by important medical publications concerning both their low precision and their invasive procedures. Based on this scenario, the FootScanAge method was conceived, seeking to determine the GA through digital imaging of the newborn plantar surface. To support the evaluation and evolution of this new method, it was developed an Open Source and Java based Decision Support System that combines Data Mining and Image Processing techniques to implement the FootScanAge method. The system was developed taking advantage of high degree of interaction between experts in neonatology and computer science.
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Keywords: | Gestational Age Determination, Image Mining, Image Processing |
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